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Quantitative and qualitative experiments demonstrate better reconstruction quality and coverage compared to existing methods, as well as strong generalization to real-world data, leading to visually appealing and structurally plausible tree point cloud representations that can be integrated into interactive digital 3D maps. 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This project aims to realize an interactive scenario-based simulation framework with integrated microclimate simulation, data analysis, and visualization for decision support in urban planning. We want to enable workflows for planning mitigation measures interactively during a live session. This requires significant advancements in the execution of and interaction with simulation scenarios and insightful visualization of the resulting data, which we will research in this project.

\n

One goal of this project is designing a highly efficient urban microclimate model system and its integration into a dynamic data flow system enabling interactive simulation steering. We seek to adapt PALM-4U, the state-of-the-art climate model system PALM 6.0 for applications in urban areas, to multi-GPU systems in order to combine its high reliability and functionality with the high computational performance needed for interactive workflows. For even higher performance in tasks that do not require the highest accuracy, such as parameter space exploration, we aim at a surrogate model based on a neural network to provide near-instant feedback.

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Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

\r\n", "abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

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}, { "publ_id": "Zezulka-2026-FGTS", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Zezulka-2026-GridThermalSim", "field_id": "supervisor", "ordernum": 2 }, { "publ_id": "zhang-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "ZL_2011_IVIG", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "zsolnai-feher-thesis-2019", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=193", "__class": "Author" } ], "articleno": "8", "doi": "10.1111/cgf.70214", "issn": "1467-8659", "journal": "Computer Graphics Forum", "note": "https://github.com/m-schuetz/Splatshop", "number": "8", "open_access": "yes", "pages": "12", "publisher": "WILEY", "volume": "44", "research_areas": [ { "id": "Rendering", "drupal_id": 4134, "name": "Rendering", "short_abstract": "In this area, we concentrate on algorithms that synthesize images to depict 3D models or scenes, often by simulating or approximating the physics of light.", "abstract": "The rendering of 3D models and scenes has been a major, long-standing challenge in computer graphics that can be divided into two major subfields. Real-time rendering refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of physically based rendering focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. Another aspect of our research work revolves around tools that facilitate the work of content creators.", "website": "https://www.cg.tuwien.ac.at/research/area/Rendering", "teaser": { "name": "teaser.png", "path": "research_area:Rendering", "type": "image/png", "size": 5244928, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Rendering/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "2011scherzerE", "2018_Mautner_Praktikum", "ABG25", "Adorjan-2015", "agyemang-2021-bsdfproxyppg", "Ams25", "antes-g", "arikan-2014-pcvis", "arikan-2015-dmrt", "Artusi-2003-Del", "ASCHL-2022-OTV", "Auzinger_2012_AAA", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", "Auzinger_2014_DCGI", "Auzinger_2014_UJA", "Auzinger-2015-IST", "bagar2010", "balvan-g", "Bauer_Dominik_2018_VR", "BAUER-2024-PWG", "BAUER-2025-PCW", "bernhard-2011-bmtf", 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"zsolnai-ist-invited-2014", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "projects": [ "3DSpatialization", "d9259", "d9275", "d9555", "Desiree", "EVOCATION", "GameTools", "GPV", "Harvest4D", "Mofa", "OpenData", "PathSpace", "REPLICATE", "RESHADE", "Scanopy", "TERAPOINTS", "Treelumination" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Rendering", "__class": "ResearchArea" } ], "keywords": [ "gaussian splats", "point clouds", "real-time rendering" ], "weblinks": [], "files": [ { "description": null, "filetitle": "cover", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1276, "image_height": 691, "name": "schuetz-2025-splatshop-cover.jpg", "type": "image/jpeg", "size": 327472, "path": "Publication:schuetz-2025-splatshop", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/schuetz-2025-splatshop/schuetz-2025-splatshop-cover.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/schuetz-2025-splatshop/schuetz-2025-splatshop-cover:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "d9275", "workgroup_id": "vis", "drupal_id": 9275, "drupal_path": "/research/projects/IVILPC", "name": "Instant Visualization and Interaction for Large Point Clouds", "name_de": null, "short_title": "IVILPC", "website": null, "status": "active", "short_abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

\r\n", "abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

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"kreuzer-2016-isf", "KREUZER-2017-PBF", "kristmann-2022-occ", "kristmann-2023-vkl", "KRISTMANN-24-JPG", "kristmann-thesis", "Kroesl_2020_11_09", "Kroesl_Katharina_2016_PPT", "kroesl-2012-rtpm", "kroesl-2017-LiteMaker", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-MoD", "KROESL-2020-SVI", "kroesl-2020-XREye", "kubicek-2024-baa", "KUE11", "kuehtreiber-2010-ikph", "Kugler-2021", "kusternig-2009-rtr", "laager_florian-2013-camr", "laager_florian-2014-daa", "labschuetz-2010-bms", "labschuetz-2011-rsr", "Lan25", "landauer-2022-kido", "lang_jakob-2022-baa", "Langer_2013_ExactGeom", "lazarevic-tci", "LEHNINGER-2007-SSV", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer_2020-cag", "leimer_2020-cag", "leimer-2013-esopc", "leimer-2014-fsco", "leimer-2016-coan", "leimer-2016-rpe", "leimer-2018-sar", "leimer-2018-sar", "leimer-2023-ecd", "LEOPOLD-2017-ALG", "leopold-2019-vox", "leutschacher_2025_prj", "Liang-2023-TVR", "lipp_markus-2010-DAC", "LIPP-2007-CGA", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "LIPP-2010-PGMS", "lipp-2019-rtxq3", "LIPP-2020-PHD", "lipp-2024-val", "lipp2011a", "liu-2012-tcvd", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "Luksch_2007_RHR", "luksch_2008_asm", "luksch_2020", "LUKSCH-2009-BBC", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "Lupu-2026-Cloth", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "MAESTRI-2012-MRW", "manpreet_kainth-2012-rus", "Mantler-06-landscape", "MANTLER-2007-DMBBC", "marek-2011-normalest", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "marin-thesis", "markovich_aleksandar-2022-maa", "Martinez-2015-TTB", "maschek-2010-rts", "matt2011", "MATTAUSCH-2006-AVC", "mattausch-2007-iav", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "mattausch-2010-var", "Mattausch-2010-vcr", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "mayer_2011_cipa", "mayer_luiz-2026-baa", "MAYER-2010-MTX", "Mayer-2010-VT", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "MAYRHAUSER-2016-SCA", "mazza-2012-bakk", "Meier_2024_WIALT", "Meier_2024_WIALT", "MeierStauffer-2013-iihf", "metzger-2024-smv", "micu_2025-prj", "miklautsch_florian-baa", "MOELLINGER-2010-SD", "MORARU-2014-CPD", "mortezapoor-2022-photogrammabot", "Mortezapoor2021ssc", "Muehlbacher_2012_RRM", "Muehlbacher_2012_RTR", "MuehlbacherArbesser-2009-LMDLightcuts", "MUEHLBERGER-2010-AFSM", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2012_aachen", "musialski_2012_fice", "musialski_2016_sosp", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-prag", "musialski-2013-surcgf", "musialski-2015-ista", "musialski-2015-pixel", "musialski-2015-souos", "musialski-2015-vrvis", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "Neum03CAMR", "Neum04GCM", "neumann-2004-aip", "Neumann-2004-HOB", "neumann-2004-ipm", "neumann-2006-gamma", "neumann-sfd", "Niederreiter_2011_SM", "NIEDERREITER-2010-SIM", "NK_2011", "novak_martin-2018-baa", "Nuernberg-2011-CBO", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "ohrhallinger-stefan-2012-the", "OPPITZ-2017-3DM", "oppitz-2023-ais", "OPPTIZ-2018-IVRL", "OTEPKA-2020-PPC", "ott-rgi", "ott-va", "Pajer-2006-tmcg", "pakkanen-2026-prj", "panfili-2019-VAVR", "panfili-2021-myop", "pangerl_2013_GPD", "papantonakis-2024-rmf", "parakkat-2024-ballmerge", "parakkat-2024-ballmerge", "PARZER-2010-STELL", "PB-VRVis-2018-005", "pegrisch_2018_uvs", 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"Purgathofer_2012_IVA", "purgathofer-1988-simple", "purgathofer-2004-asp", "purgathofer-2004-comp", "purgathofer-2004-neue", "purgathofer-2004-real", "purgathofer-2004-some", "Purgathofer-2005-Ros", "Purgathofer-2005-Tub", "Purgathofer-2006-VRVis", "Purgathofer-2009-rus", "purgathofer-2010-cgtrends", "Purgathofer-2014-EurasiaGr", "radax-2008-ir", "RADAX-2010-LOD", "radax-2010-RTL", "Radax2008", "radits_2011_gahdr", "Radwan_2021_Occ", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "Rainer_2017", "rait_alexius-2021-baa", "Rait2022", "rasch_martina-2013-HDRImage", "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "RAUCH-2011-TMS", "recheis-2009-arr", "REICHHOLF-2023-HRO", "Reichinger-12", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "Reimerth_Saskia_2016_RGU", "REINALTER_2010_VIS", "reinwald-2017-baa", "reisinger-2023-iad", "Reisner_2013_RSB", "Reisner_Irene_2013_R3D", "reitsamer-2008-tsud", "resch_martin-2026-baa", "reznicek-2020-fpgaray", "richter-2020-ani", "riegler_2020_framework", "roch-2007-rtt", "Roch2006", "Roegner_RHF_2010", "ROEGNER-2014-TUI", "ROEGNER-2015-IBR", "ROESSLER-2012-OGLES", "roth_2021_vdst", "roth_vdi", "roth-2023-vlk", "rozanics-lsf", "rubik_michael-2022-baa", "Rudolf_06_IDM", "rumpelnik_martin_2020_PRM", "rumpelnik_martin_2020_PRM", "Rumpelnik_Martin-2020-NPR", "rumpelnik-2022-vlk", "rumpler_2019_PPC", "Rumpler-2019-PPC", "RUMPLER-2021-VOGL", "rumpler-2023-dcmcm", "S05", "SABADELLO-2006-HEG", "sakai_2013", "SAKAI-2015-EAPI", "sakai-2021-eif", "sakai-2024-asa", "sakai-2025-stater", "sakai-thesis", "santos-2017-dacge", "sari2008mt", "SATZER-2008", "schaffarz_2018-pra", "scharl-master-thesis", "schartmueller_2018_baa", "schaukowitsch-2013-fls", "SCHAUKOWITSCH-2015-REMOTE", "SCHAUKOWITSCH-2015-STELL", "schedl-2012-dof", "schedl-2013-gP4", "schedl-thesis", "schefcik_juergen_2015_baa", "Scheiblauer-2006-DA", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "SCHEIBLAUER-2015-WFC", "scheiblauer-thesis", "scheiblauer-thesis", "scherzer_2010a", "Scherzer-2007-PCS", "SCHERZER-2008-FSR", "scherzer-2009-isvc", "SCHERZER-2012-TCM", "scherzer-eg2010", "scherzer-thesis", "scherzer2010b", "scherzer2010d", "scherzer2010e", "scherzer2011c", "scherzer2011d", "schmid_andreas_2013-prj", "schneider-sturm-2026-mia", "schober_florian_2012_aspm", "schoerkhuber_dominik-2016-baa", "scholz_2017_bac", "schrammel_sebastian_baa", "schuetz_markus-2013-pra", "SCHUETZ-2014-RRLP", "SCHUETZ-2015-HQP", "SCHUETZ-2016-POT", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-DISS", "SCHUETZ-2021-PCC", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schulz-faf", "schwaerzler_2018_phd", "schwaerzler-2009-ass", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "SCHWAERZLER-2017-SBGM", "schwarz-2024-m2m", "Schwengerer_Mathias-2022-BGL", "seczer-2025-vrs", "seidemann-bachelor-2013", "seisenbacher-cyclesafely", "Selig_2005_WRO", "Selig-2007-VegAnim", "Semmelrath-2022-IRS", "seyr-2025-lbt", "SIETZEN-2017-BBO", "silvana_2014", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "Spechtenhauser_Florian_2013_SIU", "spelitz_stefan-2012-CDTFMR", "sperl-2013-BA", "Sperl-praktikum-2016", "spielmann-2006-ner", "spitaler-2015-pbi", "spitaler-afr-2011", "SSMW09", "stappen_SteFAS", "stappen-2019-vrs", "starnberger-cli", "stauss-2025-gfd", "steiner_2016_isad", "steiner_2016_isad", "STEINER-2006-SVC", "steiner-2013-BS", "steiner-2014-da", "steinheber-2024-oto", "steinkellner-2022-dll", "steinkellner-2024-dll", "STEINLECHNER-2019-APS", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter", "Stingl_2011_RHS", "STINGL-2009-RHS", "Stoll2020", "STREICHER-2022-DSLS", "Streicher-bachelor-2013", "STU-SR-25", "sturl_andreas-caflm", "STURN-2013-LGI", "STURN-2013-LSI", "Sturn-2013-ST", "sturn-thesis", "stutter_david-2012-kft", "subtil-2006-disp", "SUNDSTEDT-2008-ASF", "sundstedt-2013-vag", "szabo_2013_ssrr", "Tanzmeister_2011_I3D", "tatzgern-2020-sst", "telaar_sina-2026-baa", "Thann_2019_01", "themmer-2018-fbx", "thurner-2019-ani", "TK_2011", "tobler02_amrmg", "tobler02_mbpls", "tobler97_hsdasr", "TOMASCHITZ-2020-EP", "TOROMANOFF-2005-ASA", "TR 193-02-2019-4", "TR-186-2-02-04", "TR-186-2-05-05", "TR-186-2-06-02", "TR-186-2-07-01", "TR-186-2-07-09", "TR-186-2-08-09", "TR-186-2-12-01", "Tragust-2012-GMHPC", "Tragust-2014-master-thesis", "traxler-1997-TRA", "trenkwalder-2008-landscape", "trenkwalder-2013-ma", "trenovatz-lpd", "trumpf_stefan_2012", "Tucek_2018", "Tucek_Tom-2016-aai", "tumpach_barbara-pra", "ulschmid-2024-reo", "ulschmid-2025-apc", "ulschmid-phdthesis", "unterguggenberger-2010-cmph", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2023-vaw", "unterguggenberger-2024-fropo", "unterguggenberger-phdthesis", "VASCO-2019-EVR", "vasiljevic-gpc", "VASILJEVS-2018-PMPL", "vis-foa", "VOELKL-2013-RTRS", "voglreiter-2023-tro", "Voglsam_2012_RTR", "Voglsam_2013_RRT", "wagentristl_stefan-2026-baa", "wagner-2024-par", "wallner_2008_ltosd", "WALLNER-2010-CSSAO", "wallner-2015-InfoTheoryPlay", "wallner-2015-ModelingRoutinization", "Wang-2016-BAC", "wang-sifuentes-2018-cgbase", "weber_2008_sh", "WEBER-2012-MIC", "WEBER-2015-PRA", "WEBER-2015-PRA1", "weidlich_2009_REL", "weidlich-2009-dispersion", "weidlich-2009-thesis", "weiner-2010-eud", "weinzierl_2012_iism", "weinzierl_heigl-2017-wh14", "Wenigwieser2007", "werdermann-va", "WESSNER-2019-PCW", "WEYDEMANN-2014-PIC", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "weydemann-praktikum-2016", "wieser-2019-ani", "wiesinger_2020_odpr", "wiesinger_2020_odpr", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wiesinger-2023-gcg", "wildt-tci", "Wilkie-2001-Ori", "Wilkie-2004-AMS", "wilkie-2006-dfs", "wilkie-2009-cc", "Wimmer-1999-FWIa", "Wimmer-1999-FWIb", "Wimmer-2001-PBI", "Wimmer-2001-Poi", "Wimmer-2003-RTE", "Wimmer-2004-LSPM", "Wimmer-2005-HOQ", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2006-PSM", "WIMMER-2006-SIV", "WIMMER-2007-GAR", "WIMMER-2007-RTR", "WIMMER-2008-ART", "WIMMER-2008-CAR", "WIMMER-2008-PVR", "WIMMER-2009-ARTR", "WIMMER-2009-ARTR2", "WIMMER-2009-ARTR3", "WIMMER-2009-CSR", "WIMMER-2009-ITC", "WIMMER-2009-VCCG", "WIMMER-2014-DWNT", "WIMMER-2015-CGFC", "WIMMER-2015-CGMC", "WIMMER-2016-FUTURIS", "WIMMER-2016-HARVEST4D", "WIMMER-2019-CGSG", "WIMMER-2020-ASG", "wimmer-2022-acd", "wimmer-2023-acd", "Win25", "WINKLER-2013-AMO", "Winkler-2017", "WINKLER-2019-PDG", "winklhofer_christoph-2013-RRMR", "winklmueller-aso", "withalm_brigitte-2022-baa", "Woerister_2012_ACS", "wolffhardt-2026-prj", "wonka-2000-VisP", "Wonka-2001-Ins", "Wonka-2001-IV", "Wonka-2003-Ins", "WONKA-2006-GVS", "x-mas-2013", "xmas-2025", "yoo-chaeran-2025-pr", "zapotocky_2013_ma", "ZAU14", "zeilinger_matthias-2020-baa", "Zezulka_Matthias-2023-MatLabOptInterface", "Zezulka-2024-FTS", "Zezulka-2025-NRL", "Zezulka-2026-FGTS", "Zezulka-2026-GridThermalSim", "zhang_le-2010-IGA", "zhang-thesis", "ZL_2011_IVIG", "zotti-2001-dip", "zotti-2003-ash", "zotti-2005-lum", "Zotti-2005-vis", "zotti-2006-dgm", "zotti-2006-pla", "zotti-2007-eg", "zotti-2007-hdr", "zotti-2007-PhD", "zotti-2007-wscg", "ZOTTI-2016-VAA", "ZOTTI-2017-BM", "ZOTTI-2017-TSP", "zsolnai-2018-gms", "zsolnai-feher-thesis-2019", "zsolnai-ist-invited-2014", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=rend", "__class": "Workgroup" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/schuetz-2025-splatshop/", "__class": "Publication" }, { "id": "erler-2025-lidarscout", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/216864", "title": "LidarScout: Direct Out-of-Core Rendering of Massive Point Clouds", "date": "2025-06", "abstract": "Large-scale terrain scans are the basis for many important tasks, such as topographic mapping, forestry, agriculture, and infrastructure planning. The resulting point cloud data sets are so massive in size that even basic tasks like viewing take hours to days of pre-processing in order to create level-of-detail structures that allow inspecting the data set in their entirety in real time. In this paper, we propose a method that is capable of instantly visualizing massive country-sized scans with hundreds of billions of points. Upon opening the data set, we first load a sparse subsample of points and initialize an overview of the entire point cloud, immediately followed by a surface reconstruction process to generate higher-quality, hole-free heightmaps. As users start navigating towards a region of interest, we continue to prioritize the heightmap construction process to the user's viewpoint. Once a user zooms in closely, we load the full-resolution point cloud data for that region and update the corresponding height map textures with the full-resolution data. As users navigate elsewhere, full-resolution point data that is no longer needed is unloaded, but the updated heightmap textures are retained as a form of medium level of detail. Overall, our method constitutes a form of direct out-of-core rendering for massive point cloud data sets (terabytes, compressed) that requires no preprocessing and no additional disk space. Source code, executable, pre-trained model, and dataset are available at: https://github.com/cg-tuwien/lidarscout", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2456, "image_height": 1411, "name": "erler-2025-lidarscout-teaser.jpg", "type": "image/jpeg", "size": 421958, "path": "Publication:erler-2025-lidarscout", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/erler-2025-lidarscout-teaser:thumb{{size}}.png" }, "sync_repositum_override": "date,projects,articleno", "repositum_presentation_id": null, "authors": [ { "id": 1395, "drupal_id": 1078, "orcid_id": "0000-0002-2790-9279", "website": "https://www.cg.tuwien.ac.at/staff/PhilippErler", 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Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.", "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ", "website": "https://www.cg.tuwien.ac.at/research/area/Geometry", "teaser": { "name": "teaser.png", "path": "research_area:Geometry", "type": "image/png", "size": 168072, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Geometry/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "aichner-2016-sadf", "arikan-2013-osn", "ausserer-2026-baa", "balvan-rsf", "bayer_bernhard-2026-baa", "beleznai_csaba-2025-pr", "belic_dejan_pr", "bodzenta-2026-baa", "brunner_lukas_2022_ssb", "celarek-2022-gmcn", "clemenz_2019_rosy_fields", "cornel-2022-wih", "csecsy-fcd", "darovskikh_leonid-2025-prj", "deak-a3", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Doerflinger-2016-CDV", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fitzinger_andreas-daa", "forsythe-2016-ccm", "fraissl_niklas-2023-pra", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Guerrero-2014-TPS", "hamzic_ademir-baa", "harisch-mvs", "hatzinger-2026-baa", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "ILCIK-phdthesis", "jira_marcel-2024-baa", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "kazda-tmd", "Kellner-2021-DA", "kerbl-2022-trienc", "koeppel-2016-baa", "kohlhas_jakob-2023-pra", "konrad-2020-baa", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "kubicek-2024-baa", "Kugler_2019", "laager_florian-2014-daa", "lang_jakob-2022-baa", "Laschober-2018", "lazarevic-tci", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-rpe", "leimer-2018-sar", "leutschacher_2025_prj", "loeffelmann-1995-para", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "marin-2022-sig", "marin-2022-sigdt", 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"preiner_2012_AS", "preiner_2017_phd", "Preiner_2019", "preiner2014clop", "proelss-bdp", "prohaska_julia-2023-baa", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "rait_alexius-2021-baa", "REICHHOLF-2023-HRO", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "reinwald-2017-baa", "Reisner_2013_RSB", "resch_martin-2026-baa", "riegler_2020_framework", "roth_vdi", "rozanics-lsf", "rubik_michael-2022-baa", "rumpelnik_martin_2020_PRM", "schaffarz_2018-pra", "schartmueller_2018_baa", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "Schmalstieg-1996-LOB", "Schmalstieg-1997-SMO", "scholz_2017_bac", "schrammel_sebastian_baa", "SCHUETZ-2022-PCC", "schuh-2018-mesh-blending", "schulz-faf", "seisenbacher-cyclesafely", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "starnberger-cli", "steiner_2016_isad", "steinheber-2024-oto", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2025-par", "Tobler-1995-AAC", "Tobler-1995-BGD", "tobler02_amrmg", "Traxler-1996-CTB", "trenovatz-lpd", "tumpach_barbara-pra", "unterguggenberger-2021-msh", "Vucenovic_2022", "wagentristl_stefan-2026-baa", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "Wimmer-1998-SMO", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2016-HARVEST4D", "withalm_brigitte-2022-baa", "wolffhardt-2026-prj", "yoo-chaeran-2025-pr", "zeilinger_matthias-2020-baa", "Zezulka-2024-FTS" ], "projects": [ "3DSpatialization", "d4388", "d9275", "EVOCATION", "GameTools", "Harvest4D", "SCI_BIM", "ShapeAcquisition", "Superhumans", "TERAPOINTS", "WorldScale" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry", "__class": "ResearchArea" }, { "id": "Modeling", "drupal_id": 4130, "name": "Modeling", "short_abstract": "In this area, we focus on researching methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "website": "https://www.cg.tuwien.ac.at/research/area/Modeling", "teaser": { "name": "teaser.jpg", "path": "research_area:Modeling", "type": "image/jpeg", "size": 190581, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Modeling/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "AA2020", "Adorjan-2015", "aichner-2016-sadf", "arikan-2013-osn", "birsak-thesis", "Birsak2018-SA", "Brandstaetter2020", "brunner_lukas_2022_ssb", "Caic2021", "clemenz_2019_rosy_fields", "DOG10", "dusberger-2010-msm", "eibens-2021-tsgpmg", "eibensteiner-2021-pmcg", "eibner-2009-gpc", "Erhardt_2025_Scutes", "erler_2024_ppsurf", 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Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

\r\n", "abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

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"erler_2024_ppsurf", "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "erler_philipp-2017-phd", "erler_philipp-2017-phd", "ERLER-2017-HVR", "erler-2020-p2s", "erler-2020-p2s", "erler-2020-p2s", "erler-2025-lidarscout", "ERNST-2010-IOOC", "ernst-2013-fif", "ESBERGER-2016-AHO", "ESCHNER-2019-GDT", "fan-2014-scfl", "fan-2014-scfl", "Fauster-06-st", "Felberbauer_2012_AG", "fiedler-2009-php", "fiedler-2022-vlk", "fink-2012-cg1", "fink-2013-cag", "fink-2013-gvp", "Fischer-2018-sssvr", "fitzinger_andreas-daa", "fizimayer-2007-art", "fleiss-2015-da", "forsythe-2016-ccm", "FRAISS-2017-PCU", "fraiss-2019-rtx", "FRAISS-2022-CGMM", "fraissl_niklas-2023-pra", "freude_2020_rs", "Freude_MSc", "FREUDE-2015-phd", "freude-2023-prh", "freude-2023-prh", "freude-2023-sem", "freude-2023-sem", "freude-2025-iso", "freude-2025-iso", "freude-2025-ras", "Fritz-2012", "fruehstueck-2008-gpu", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "Fuericht-2026-FPD", "Fuerst_2014_BSc", "Fuerst-2009-dfr", "FUERST-2013-RTWS", "Fuerst-Bachelor-2013", "G_P_06_RFS", "GAHR-2013-AGM", "gamper_2008_or", "GAMPER-2018-OSG", "gamsjaeger-2022-proc", "gangl-2018-cgbase", "GANTNER-2018-ARO", "GANTNER-2019-CRS", "GEBHART-2008-AGV", "gersthofer_2017_COP", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "geyer_lukas-2014-bat", "geyer-2018-apbf", "giefing_juergen-2013-ba", "GIEGL-2006-QVS", "GIEGL-2007-FVS", "GIEGL-2007-QV1", "GIEGL-2007-UNP", "gilmutdinov-2022-aomlbwug", "glanz-2017-pbrcomparison", "goel-2024-rdr", "goetz_johann-cagmfp", "Goldmann_2011_GPU", "gramegna-rfr", "Grasberger_08_VV", "Grasberger_2008_ISR", "grasberger_2009_CSB", "GRELAUD-2009-EPA", "GRIESHOFER-2018-GOS", "Grisenti-2026-HSHPG", "grosse-2009-avp", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Gruber2019", "Guerrero_Paul_2014_EPG", "guerrero-2008-dip", "guerrero-2008-sli", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "gurtler-2014-ssggm", "Gusenbauer_Matthias_2015_ANM", "Habel_07_xms", "Habel_08_SSH", "Habel_09_PGT", "Habel_09_PGT", "Habel_2007_IAG", "Habel_2007_RTT", "Habel_2009_PhD", "Habel_2012_PSP", "Habel_LSN_2011", "Habel_RAV_2010", "Habel-09-RAT", "Habel-09-THB", "Habel-2010-EIN", "hafner_christian-2013-oflow", "hafner-2015-eigf", "HAFNER-2015-FEM", "hafner-2015-onff", "halbritter-2024-m2m", "hamzic_ademir-baa", "hanko-2019-ani", "HANN_2022_IPT", "harisch-mvs", "Hartl_2006_OgC", "hasbay-2026-tfo", "hatzinger-2026-baa", "hauer_alex-2013-ba", "havran-2005-egsr", "havran-2005-sccg", "havran-2006-tut", "Hebart-2011-ColorAdjustment", "HECHER-2010-3DS", "hecher-2012-MH", "hecher-2014-MH", "HECHER-2017-HDY", "heinz-2019-psi", "heiss-rfr", "herzberger-2021-cmake", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "Holzer-06-HDR", "Honic_2021", "hornacek-2010-evp", "horvath_imp", "houska-2020-IPGM", "HU-2017-ETM", "huber-2025-esl", "huerbe-2019-BA", "HUMMEL-2001-MSE", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2011-pmous", "ilcik-2013-cipmi", "ilcik-2013-pmsg", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ILCIK-phdthesis", "ilcikova-thesis", "intel2016", "ioannis-2026-sro", "Ishmukhametov_Denis_2011_EIN", "jafari-2023-avk", "jahrmann_klemens_KFR", "JAHRMANN-2013-IGR", "JAHRMANN-2015-GRASS", "JAHRMANN-2016-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-AIP", "jeschke-05-ARI", "jeschke-05-ISTAR", "jeschke-09-praguetalk", "jeschke-09-rendering", "jeschke-09-solver", "Jeschke-2002-LEM", "Jeschke-2002-LEMA", "Jeschke-2002-TDM", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "jeschke-2010-diff", "jeschke-2011-est", "jeschke-2011-esttalk", "jeschke-2011-talkPrague", "Jia-thesis", "Jimenez_SSS_2015", "jira_marcel-2024-baa", "JORDAKIEVA-2017-VFR", "KAFKA-2014-19MRD", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "karampekios_anastasios-prj", "Kathi-2018-VRB", "kazda-tmd", "Keilman2022", "kendlbacher-2016", "kenzel_michael_2021_cuda", "kerbl_2019_planet_poster", "kerbl_2021_hdg", "kerbl-2020-improvencoding", "kerbl-2022-cuda", "kerbl-2022-trienc", "kimmersdorfer-2021-mzip", "kimmersdorfer-2024-vcpr", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "KLAUS-2020-PCC", "klein-2020-rtgi", "kment_2008_cc", "knecht_2013_RSM", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "Knecht_Schwaerzler_2008_ash", "knecht-2007-ao", "knecht-2009-MKN", "knecht-2009-TAS", "knecht-2011-CBCM", "knoetzl_alexander-2025-prj", "koch-2019-PR", "KOCH-2021-GVS", "KOCH-2021-GVSDA", "koenigsberger-2024-msu", "koeppel-2016-baa", "Koeppl-2023-DLO", "koessler-2013-BA", "Kogelnig_Philip-2008-OGC", "kohlhas_jakob-2023-pra", "Kollmann-2015-DoF", "komon-2026-rso", "Komon2022", "konrad-2020-baa", "Kovacs_2017", "kovacs-2023-ttm", "kovacs-2025-pf", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "KREUZER-2014-DPA", "KREUZER-2015-DPA", "kreuzer-2016-isf", "KREUZER-2017-PBF", "kristmann-2022-occ", "kristmann-2023-vkl", "KRISTMANN-24-JPG", "kristmann-thesis", "Kroesl_2020_11_09", "Kroesl_Katharina_2016_PPT", "kroesl-2012-rtpm", "kroesl-2017-LiteMaker", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-MoD", "KROESL-2020-SVI", "kroesl-2020-XREye", "kubicek-2024-baa", "KUE11", "kuehtreiber-2010-ikph", "Kugler-2021", "kusternig-2009-rtr", "laager_florian-2013-camr", "laager_florian-2014-daa", "labschuetz-2010-bms", "labschuetz-2011-rsr", "Lan25", "landauer-2022-kido", "lang_jakob-2022-baa", "Langer_2013_ExactGeom", "lazarevic-tci", "LEHNINGER-2007-SSV", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer_2020-cag", "leimer_2020-cag", "leimer-2013-esopc", "leimer-2014-fsco", "leimer-2016-coan", "leimer-2016-rpe", "leimer-2018-sar", "leimer-2018-sar", "leimer-2023-ecd", "LEOPOLD-2017-ALG", "leopold-2019-vox", "leutschacher_2025_prj", "Liang-2023-TVR", "lipp_markus-2010-DAC", "LIPP-2007-CGA", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "LIPP-2010-PGMS", "lipp-2019-rtxq3", "LIPP-2020-PHD", "lipp-2024-val", "lipp2011a", "liu-2012-tcvd", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "Luksch_2007_RHR", "luksch_2008_asm", "luksch_2020", "LUKSCH-2009-BBC", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "Lupu-2026-Cloth", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "MAESTRI-2012-MRW", "manpreet_kainth-2012-rus", "Mantler-06-landscape", "MANTLER-2007-DMBBC", "marek-2011-normalest", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "marin-thesis", "markovich_aleksandar-2022-maa", "Martinez-2015-TTB", "maschek-2010-rts", "matt2011", "MATTAUSCH-2006-AVC", "mattausch-2007-iav", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "mattausch-2010-var", "Mattausch-2010-vcr", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "mayer_2011_cipa", "mayer_luiz-2026-baa", "MAYER-2010-MTX", "Mayer-2010-VT", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "MAYRHAUSER-2016-SCA", "mazza-2012-bakk", "Meier_2024_WIALT", "Meier_2024_WIALT", "MeierStauffer-2013-iihf", "metzger-2024-smv", "micu_2025-prj", "miklautsch_florian-baa", "MOELLINGER-2010-SD", "MORARU-2014-CPD", "mortezapoor-2022-photogrammabot", "Mortezapoor2021ssc", "Muehlbacher_2012_RRM", "Muehlbacher_2012_RTR", "MuehlbacherArbesser-2009-LMDLightcuts", "MUEHLBERGER-2010-AFSM", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2012_aachen", "musialski_2012_fice", "musialski_2016_sosp", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-prag", "musialski-2013-surcgf", "musialski-2015-ista", "musialski-2015-pixel", "musialski-2015-souos", "musialski-2015-vrvis", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "Neum03CAMR", "Neum04GCM", "neumann-2004-aip", "Neumann-2004-HOB", "neumann-2004-ipm", "neumann-2006-gamma", "neumann-sfd", "Niederreiter_2011_SM", "NIEDERREITER-2010-SIM", "NK_2011", "novak_martin-2018-baa", "Nuernberg-2011-CBO", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "ohrhallinger-stefan-2012-the", "OPPITZ-2017-3DM", "oppitz-2023-ais", "OPPTIZ-2018-IVRL", "OTEPKA-2020-PPC", "ott-rgi", "ott-va", "Pajer-2006-tmcg", "pakkanen-2026-prj", "panfili-2019-VAVR", "panfili-2021-myop", "pangerl_2013_GPD", "papantonakis-2024-rmf", "parakkat-2024-ballmerge", "parakkat-2024-ballmerge", "PARZER-2010-STELL", "PB-VRVis-2018-005", "pegrisch_2018_uvs", "Pel-2026", "PERNDORFER-2015-ECS", "pernsteiner-2022-msh", "pernsteinre_jakob_2020_eechc", "perzi_marvin-2026-baa", "Petersen_Viktoria-2024-SBO", "pezenka_lukas2012-bspcga", "pichler_2022_fro", "pichler_2022_fro", "PIRINGER-2003-HBOQ", "pirraku-f", "piskernik-2010-eud", "pistellato-2023-elp", "PLUCH-2009-ANP", "PODARAS-2017-ACRS", "Podaras-praktikum-2016", "pogrzebacz-2014-gggm", "pogrzebacz-2023-vkl", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "POLLAK-2016-STEREO", "polzer-sog", "pr10", "praeauer-2011-et", "Prast_Stefanie_2013-CLG", "preiner_2010_GIPC", "preiner_2012_AS", "preiner_2012_AS", "Preiner_2019", "PREINER-2009-GIPC", "preiner11IR", "preiner2014clop", "preissegger-2025-vrh", "Preymann-2022-pytamashii", "prieler_11_patchmatch", "prieler_daniel-2013-da", "prieler_daniel-2013-pra", "probst_kolesik_2010_pk10", "probst-2023-para", "proelss-bdp", "prohaska_julia-2023-baa", "prost-2016-molecule", "PROST-2019-RTPAL", "Przemyslaw_Gora_2016_UVU", "PUEYO-2019-SCL", "Purgathofer_2012_IVA", "purgathofer-1988-simple", "purgathofer-2004-asp", "purgathofer-2004-comp", "purgathofer-2004-neue", "purgathofer-2004-real", "purgathofer-2004-some", "Purgathofer-2005-Ros", "Purgathofer-2005-Tub", "Purgathofer-2006-VRVis", "Purgathofer-2009-rus", "purgathofer-2010-cgtrends", "Purgathofer-2014-EurasiaGr", "radax-2008-ir", "RADAX-2010-LOD", "radax-2010-RTL", "Radax2008", "radits_2011_gahdr", "Radwan_2021_Occ", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "Rainer_2017", "rait_alexius-2021-baa", "Rait2022", "rasch_martina-2013-HDRImage", "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "RAUCH-2011-TMS", "recheis-2009-arr", "REICHHOLF-2023-HRO", "Reichinger-12", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "Reimerth_Saskia_2016_RGU", "REINALTER_2010_VIS", "reinwald-2017-baa", "reisinger-2023-iad", "Reisner_2013_RSB", "Reisner_Irene_2013_R3D", "reitsamer-2008-tsud", "resch_martin-2026-baa", "reznicek-2020-fpgaray", "richter-2020-ani", "riegler_2020_framework", "roch-2007-rtt", "Roch2006", "Roegner_RHF_2010", "ROEGNER-2014-TUI", "ROEGNER-2015-IBR", "ROESSLER-2012-OGLES", "roth_2021_vdst", "roth_vdi", "roth-2023-vlk", "rozanics-lsf", "rubik_michael-2022-baa", "Rudolf_06_IDM", "rumpelnik_martin_2020_PRM", "rumpelnik_martin_2020_PRM", "Rumpelnik_Martin-2020-NPR", "rumpelnik-2022-vlk", "rumpler_2019_PPC", "Rumpler-2019-PPC", "RUMPLER-2021-VOGL", "rumpler-2023-dcmcm", "S05", "SABADELLO-2006-HEG", "sakai_2013", "SAKAI-2015-EAPI", "sakai-2021-eif", "sakai-2024-asa", "sakai-2025-stater", "sakai-thesis", "santos-2017-dacge", "sari2008mt", "SATZER-2008", "schaffarz_2018-pra", "scharl-master-thesis", "schartmueller_2018_baa", "schaukowitsch-2013-fls", "SCHAUKOWITSCH-2015-REMOTE", "SCHAUKOWITSCH-2015-STELL", "schedl-2012-dof", "schedl-2013-gP4", "schedl-thesis", "schefcik_juergen_2015_baa", "Scheiblauer-2006-DA", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "SCHEIBLAUER-2015-WFC", "scheiblauer-thesis", "scheiblauer-thesis", "scherzer_2010a", "Scherzer-2007-PCS", "SCHERZER-2008-FSR", "scherzer-2009-isvc", "SCHERZER-2012-TCM", "scherzer-eg2010", "scherzer-thesis", "scherzer2010b", "scherzer2010d", "scherzer2010e", "scherzer2011c", "scherzer2011d", "schmid_andreas_2013-prj", "schneider-sturm-2026-mia", "schober_florian_2012_aspm", "schoerkhuber_dominik-2016-baa", "scholz_2017_bac", "schrammel_sebastian_baa", "schuetz_markus-2013-pra", "SCHUETZ-2014-RRLP", "SCHUETZ-2015-HQP", "SCHUETZ-2016-POT", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-DISS", "SCHUETZ-2021-PCC", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schulz-faf", "schwaerzler_2018_phd", "schwaerzler-2009-ass", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "SCHWAERZLER-2017-SBGM", "schwarz-2024-m2m", "Schwengerer_Mathias-2022-BGL", "seczer-2025-vrs", "seidemann-bachelor-2013", "seisenbacher-cyclesafely", "Selig_2005_WRO", "Selig-2007-VegAnim", "Semmelrath-2022-IRS", "seyr-2025-lbt", "SIETZEN-2017-BBO", "silvana_2014", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "Spechtenhauser_Florian_2013_SIU", "spelitz_stefan-2012-CDTFMR", "sperl-2013-BA", "Sperl-praktikum-2016", "spielmann-2006-ner", "spitaler-2015-pbi", "spitaler-afr-2011", "SSMW09", "stappen_SteFAS", "stappen-2019-vrs", "starnberger-cli", "stauss-2025-gfd", "steiner_2016_isad", "steiner_2016_isad", "STEINER-2006-SVC", "steiner-2013-BS", "steiner-2014-da", "steinheber-2024-oto", "steinkellner-2022-dll", "steinkellner-2024-dll", "STEINLECHNER-2019-APS", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter", "Stingl_2011_RHS", "STINGL-2009-RHS", "Stoll2020", "STREICHER-2022-DSLS", "Streicher-bachelor-2013", "STU-SR-25", "sturl_andreas-caflm", "STURN-2013-LGI", "STURN-2013-LSI", "Sturn-2013-ST", "sturn-thesis", "stutter_david-2012-kft", "subtil-2006-disp", "SUNDSTEDT-2008-ASF", "sundstedt-2013-vag", "szabo_2013_ssrr", "Tanzmeister_2011_I3D", "tatzgern-2020-sst", "telaar_sina-2026-baa", "Thann_2019_01", "themmer-2018-fbx", "thurner-2019-ani", "TK_2011", "tobler02_amrmg", "tobler02_mbpls", "tobler97_hsdasr", "TOMASCHITZ-2020-EP", "TOROMANOFF-2005-ASA", "TR 193-02-2019-4", "TR-186-2-02-04", "TR-186-2-05-05", "TR-186-2-06-02", "TR-186-2-07-01", "TR-186-2-07-09", "TR-186-2-08-09", "TR-186-2-12-01", "Tragust-2012-GMHPC", "Tragust-2014-master-thesis", "traxler-1997-TRA", "trenkwalder-2008-landscape", "trenkwalder-2013-ma", "trenovatz-lpd", "trumpf_stefan_2012", "Tucek_2018", "Tucek_Tom-2016-aai", "tumpach_barbara-pra", "ulschmid-2024-reo", "ulschmid-2025-apc", "ulschmid-phdthesis", "unterguggenberger-2010-cmph", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2023-vaw", "unterguggenberger-2024-fropo", "unterguggenberger-phdthesis", "VASCO-2019-EVR", "vasiljevic-gpc", "VASILJEVS-2018-PMPL", "vis-foa", "VOELKL-2013-RTRS", "voglreiter-2023-tro", "Voglsam_2012_RTR", "Voglsam_2013_RRT", "wagentristl_stefan-2026-baa", "wagner-2024-par", "wallner_2008_ltosd", "WALLNER-2010-CSSAO", "wallner-2015-InfoTheoryPlay", "wallner-2015-ModelingRoutinization", "Wang-2016-BAC", "wang-sifuentes-2018-cgbase", "weber_2008_sh", "WEBER-2012-MIC", "WEBER-2015-PRA", "WEBER-2015-PRA1", "weidlich_2009_REL", "weidlich-2009-dispersion", "weidlich-2009-thesis", "weiner-2010-eud", "weinzierl_2012_iism", "weinzierl_heigl-2017-wh14", "Wenigwieser2007", "werdermann-va", "WESSNER-2019-PCW", "WEYDEMANN-2014-PIC", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "weydemann-praktikum-2016", "wieser-2019-ani", "wiesinger_2020_odpr", "wiesinger_2020_odpr", "wiesinger_2025-baa", 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"Wonka-2003-Ins", "WONKA-2006-GVS", "x-mas-2013", "xmas-2025", "yoo-chaeran-2025-pr", "zapotocky_2013_ma", "ZAU14", "zeilinger_matthias-2020-baa", "Zezulka_Matthias-2023-MatLabOptInterface", "Zezulka-2024-FTS", "Zezulka-2025-NRL", "Zezulka-2026-FGTS", "Zezulka-2026-GridThermalSim", "zhang_le-2010-IGA", "zhang-thesis", "ZL_2011_IVIG", "zotti-2001-dip", "zotti-2003-ash", "zotti-2005-lum", "Zotti-2005-vis", "zotti-2006-dgm", "zotti-2006-pla", "zotti-2007-eg", "zotti-2007-hdr", "zotti-2007-PhD", "zotti-2007-wscg", "ZOTTI-2016-VAA", "ZOTTI-2017-BM", "ZOTTI-2017-TSP", "zsolnai-2018-gms", "zsolnai-feher-thesis-2019", "zsolnai-ist-invited-2014", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=rend", "__class": "Workgroup" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/erler-2025-lidarscout/", "__class": "Publication" }, { "id": "ulschmid-2025-apc", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/215609", "title": "Automated Prioritization for Context-Aware Re-rendering in Editing", "date": "2025", "abstract": "Real-time Monte Carlo path tracing has become a feasible option for interactive 3D scene editing due to recent advancements in GPU ray tracing performance, as well as (AI-accelerated) denoising techniques. While it is thus gaining increasing support in popular modeling software, even minor edits such as adjusting materials or moving small objects typically require current solutions to discard previous samples and restart the image formation process from scratch. A recent solution introduced two adaptive, priority-based re-rendering techniques implementing incremental updates while focusing first on reconstructing regions of high importance and gradually addressing less critical areas. An extensive user study compared these prioritized renderings with conventional same-time re-rendering to evaluate their effectiveness for interactive scene editing. Results indicate a significant preference for incremental rendering techniques for editing small objects over traditional full-screen re-rendering with denoising, even with basic priority policies. Building upon these results, we revisit the underlying design choices and derive more sophisticated priority policies that respect global illumination effects (shadows and reflections) as well as employing attention-based techniques (based either on eye tracking to prioritize areas in the user’s gaze or, alternatively, using the cursor position).", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1501, "image_height": 930, "name": "ulschmid-2025-apc-image.webp", "type": "image/webp", "size": 91268, "path": "Publication:ulschmid-2025-apc", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ulschmid-2025-apc/ulschmid-2025-apc-image.webp", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/ulschmid-2025-apc/ulschmid-2025-apc-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1954, "drupal_id": 4406, "orcid_id": "0000-0002-0539-9378", "website": "https://www.cg.tuwien.ac.at/staff/AnnalenaUlschmid", "firstname": "Annalena", "lastname": "Ulschmid", "searchname": "Annalena Ulschmid", "is_teacher": false, "name": "Annalena Ulschmid", "publications": [ "ecormier-nocca-2025-sls", "huber-2025-esl", "ulschmid-2024-reo", "ulschmid-2025-apc", "ulschmid-phdthesis", "unterguggenberger-2023-ait" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "ABG25", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "akan-vf", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Ams25", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "antes-g", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "balvan-g", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Che-2025", "field_id": "co_supervisor", "ordernum": 0 }, { 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Real-time rendering refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of physically based rendering focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. Another aspect of our research work revolves around tools that facilitate the work of content creators.", "website": "https://www.cg.tuwien.ac.at/research/area/Rendering", "teaser": { "name": "teaser.png", "path": "research_area:Rendering", "type": "image/png", "size": 5244928, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Rendering/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "2011scherzerE", "2018_Mautner_Praktikum", "ABG25", "Adorjan-2015", "agyemang-2021-bsdfproxyppg", "Ams25", "antes-g", "arikan-2014-pcvis", "arikan-2015-dmrt", "Artusi-2003-Del", "ASCHL-2022-OTV", "Auzinger_2012_AAA", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", "Auzinger_2014_DCGI", "Auzinger_2014_UJA", "Auzinger-2015-IST", "bagar2010", "balvan-g", "Bauer_Dominik_2018_VR", "BAUER-2024-PWG", "BAUER-2025-PCW", "bernhard-2011-bmtf", 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"zsolnai-ist-invited-2014", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "projects": [ "3DSpatialization", "d9259", "d9275", "d9555", "Desiree", "EVOCATION", "GameTools", "GPV", "Harvest4D", "Mofa", "OpenData", "PathSpace", "REPLICATE", "RESHADE", "Scanopy", "TERAPOINTS", "Treelumination" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Rendering", "__class": "ResearchArea" } ], "keywords": [ "Path Tracing", "Scene editing", "Adaptive rendering", "empirical studies" ], "weblinks": [ { "href": "https://github.com/cg-tuwien/Prioritized-ReRendering", "caption": "GitHub", "description": "GitHub", "main_file": 1 } ], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1501, "image_height": 930, "name": "ulschmid-2025-apc-image.webp", "type": "image/webp", "size": 91268, "path": "Publication:ulschmid-2025-apc", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ulschmid-2025-apc/ulschmid-2025-apc-image.webp", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/ulschmid-2025-apc/ulschmid-2025-apc-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "ulschmid-2025-apc-paper.pdf", "type": "application/pdf", "size": 1866148, "path": "Publication:ulschmid-2025-apc", "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ulschmid-2025-apc/ulschmid-2025-apc-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2025/ulschmid-2025-apc/ulschmid-2025-apc-paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "d4314", "workgroup_id": "rend", "drupal_id": 4314, "drupal_path": "/research/projects/ACD", "name": "Advanced Computational Design", "name_de": "Advanced Computational Design", "short_title": "ACD", "website": "http://acd.tuwien.ac.at", "status": "active", "short_abstract": null, "abstract": "

Research question: The main research question addressed by the SFB “Advanced Computational Design” is how to advance design tools and processes through multi- and interdisciplinary basic research in the areas of digital architecture, integrated building design, computer graphics and virtual reality, discrete and applied geometry, and computational mechanics. 

\n

Wider research context: Architecture, Engineering and Construction (AEC) shapes our built environment, exerting substantial environmental, cultural and economic influence on society. However, it is among the least digitized industries, still caught in silo-thinking and sequential planning processes. The Information and Communication Technology field, on the other hand, is highly innovative, creating digital design tools that are well-founded in basic research, but often lack relevant domain knowledge, thus hardly meeting designers’ needs.

\n

Innovation: We will connect architecture, computer science, mathematics and engineering in order to develop advanced computational design tools able to incorporate implicit and explicit design knowledge. This unique combination of scientific disciplines and collaborative research with strong theoretical foundations aims to bring radical innovation in computational design by allowing immediate feedback already in early design phases and by expanding solution spaces by computing design variants that cannot be found by current methods.

\n

Approach: The proposed research is structured in three areas: Design Methodology (A1), Visual and Haptic Design Interaction (A2) and Form Finding (A3). A1 uses ontologies to describe AEC design semantics, coupled to a novel digital mixed-reality sketchbook, and an innovative implicit modeling approach based on retrieving and enhancing 2D images and 3D point clouds through transfer learning. A1 also acts as a platform for integrating and evaluating the computational tools and methods developed in A2 and A3. These areas will investigate research questions in computational design involving algorithmic solutions. A2 investigates real-time global-illumination and optimization algorithms for lighting design, as well as a new method for large-scale haptic interactions in virtual reality based on a mobile robotic platform. In A3, form finding will be explored regarding geometric, mechanical and material constraints, in particular: paneling of complex shapes by patches of certain surface classes while optimizing the number of molds; algorithms for finding new transformable quad-surfaces; mechanical models for an efficient simulation of bio-composite material systems. Furthermore, new ways of form-finding will be explored experimentally, which will allow for validating the developed algorithmic approaches and reconsidering model assumptions and constraints.

\n

Added value: The fundamental computational tools and methods to be developed will be applicable in AEC and other fields of the creative industries.

", "start_date": "2020-03-01", "end_date": "2028-02-29", "leader_id": 193, "logo": null, "funding_organisations": [], "research_areas": [], "publications": [ "Derflinger-2026-RTTW2", "ecormier-nocca-2025-sls", "Erhardt_2025_Scutes", "Erhardt_Seirlehner-2024-TamashiiIntegration", "freude-2023-prh", "freude-2023-sem", "freude-2025-iso", "Fuericht-2026-FPD", "Grisenti-2026-HSHPG", "huber-2025-esl", "koenigsberger-2024-msu", "Koeppl-2023-DLO", "kovacs-2023-ttm", "landauer-2022-kido", "LIPP-2020-PHD", "lipp-2024-val", "Meier_2024_WIALT", "mortezapoor-2022-photogrammabot", "Mortezapoor2021ssc", "Preymann-2022-pytamashii", "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "reisinger-2023-iad", "Schwengerer_Mathias-2022-BGL", "steinkellner-2022-dll", "ulschmid-2024-reo", "ulschmid-2025-apc", "unterguggenberger-2023-vaw", "wimmer-2022-acd", "wimmer-2023-acd", "Zezulka_Matthias-2023-MatLabOptInterface", "Zezulka-2025-NRL", "Zezulka-2026-FGTS", "Zezulka-2026-GridThermalSim", "zhang-thesis" ], "url": "https://www.cg.tuwien.ac.at/research/projects/ACD", "__class": "Project" }, { "id": "d9275", "workgroup_id": "vis", "drupal_id": 9275, "drupal_path": "/research/projects/IVILPC", "name": "Instant Visualization and Interaction for Large Point Clouds", "name_de": null, "short_title": "IVILPC", "website": null, "status": "active", "short_abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

\r\n", "abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

\r\n", "start_date": "2023-07-02", "end_date": "2026-07-01", "leader_id": 166, "logo": { "name": "logo.png", "path": "project:d9275", "type": "image/png", "size": 268858, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/d9275/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [], "research_areas": [ "Geometry", "Rendering", "VR" ], "publications": [ "erler-2025-lidarscout", "goel-2024-rdr", "grammatikaki-2026-treeon", "kerbl-2024-ah3", "papantonakis-2024-rmf", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "ulschmid-2024-reo", "ulschmid-2025-apc", "unterguggenberger-2024-fropo", "voglreiter-2023-tro" ], "url": "https://www.cg.tuwien.ac.at/research/projects/IVILPC", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2025/ulschmid-2025-apc/", "__class": "Publication" }, { "id": "goel-2024-rdr", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/204000", "title": "Real-Time Decompression and Rasterization of Massive Point Clouds", "date": "2024-08-09", "abstract": "Large-scale capturing of real-world scenes as 3D point clouds (e.g., using LIDAR scanning) generates billions of points that are challenging to visualize. High storage requirements prevent the quick and easy inspection of captured datasets on user-grade hardware. The fastest real-time rendering methods are limited by the available GPU memory and render only around 1 billion points interactively. We show that we can achieve state-of-the-art in both while simultaneously supporting datasets that surpass the capabilities of other methods. We present an on-the-fly point cloud decompression scheme that tightly integrates with software rasterization to reduce on-chip memory requirements by more than 4×. Our method compresses geometry losslessly and provides high visual quality at real-time framerates. We use a GPU-friendly, clipped Huffman encoding for compression. Point clouds are divided into equal-sized batches, which are Huffman-encoded independently. Batches are further subdivided to form easy-to-consume streams of data for massively parallel execution. The compressed point clouds are stored in an access-aware manner to achieve coherent GPU memory access and a high L1 cache hit rate at render time. Our approach can decompress and rasterize up to 120 million Huffman-encoded points per millisecond on-the-fly. We evaluate the quality and performance of our approach on various large datasets against the fastest competing methods. Our approach renders massive 3D point clouds at competitive frame rates and visual quality while consuming significantly less memory, thus unlocking unprecedented performance for the visualization of challenging datasets on commodity GPUs.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "cover", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1695, "image_height": 961, "name": "goel-2024-rdr-cover.jpg", "type": "image/jpeg", "size": 276042, "path": "Publication:goel-2024-rdr", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/goel-2024-rdr/goel-2024-rdr-cover.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/goel-2024-rdr/goel-2024-rdr-cover:thumb{{size}}.png" }, "sync_repositum_override": "projects,date_from,date_to,event,lecturer,location", "repositum_presentation_id": null, "authors": [ { "id": 5402, "drupal_id": null, "orcid_id": "0000-0002-9564-4022", "website": null, "firstname": "Rahul", "lastname": "Goel", "searchname": "Rahul Goel", "is_teacher": false, "name": "Rahul Goel", "publications": [ "goel-2024-rdr" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5402", "__class": "Author" }, { "id": 1116, "drupal_id": 302, "orcid_id": "0000-0002-8166-3089", "website": "https://www.cg.tuwien.ac.at/staff/MarkusSchütz", "firstname": "Markus", "lastname": "Schütz", "searchname": "Markus Schütz", "is_teacher": false, "name": "Markus Schütz", "publications": [ "erler-2025-lidarscout", "goel-2024-rdr", "kroesl_x_card_2017", "Martinez-2015-TTB", "OTEPKA-2020-PPC", "schuetz_markus-2013-pra", "SCHUETZ-2014-RRLP", "SCHUETZ-2015-HQP", "SCHUETZ-2016-POT", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2019-PCC", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-DISS", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schuetz-mb", "TR 193-02-2019-4", "TR 193-2-2019-4", "unterguggenberger-2024-fropo" ], "publications_first": [], "project_leader": [ "d9691" ], "publication_field": [ { "publ_id": "BAUER-2024-PWG", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "BAUER-2025-PCW", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "ERLER-2017-HVR", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "FRAISS-2017-PCU", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "gersthofer_2017_COP", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "goel-2024-rdr", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "ioannis-2026-sro", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "KLAUS-2020-PCC", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "KLAUS-2020-PCC", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "KRISTMANN-24-JPG", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "probst-2023-para", "field_id": "supervisor", "ordernum": 2 }, { "publ_id": "rumpler_2019_PPC", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Rumpler-2019-PPC", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "RUMPLTER_2019-LVR", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "SCHUETZ-2015-HQP", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "schuetz-2019-CLOD", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "SCHUETZ-2020-MPC", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "schuetz-2020-PPC", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "SCHUETZ-2021-PCC", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "SCHUETZ-2022-PCC", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "SCHUETZ-2023-LOD", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "SCHUETZ-2024-SIMLOD", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "sippl_tobias_2017_WPC", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "SIPPL-2017-POS", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "VASCO-2019-EVR", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "WESSNER-2019-PCW", "field_id": "supervisor", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1116", "__class": "Author" }, { "id": 5403, "drupal_id": null, "orcid_id": "0000-0002-7164-4917", "website": null, "firstname": "P. 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"ordernum": 1 }, { "publ_id": "Rumpelnik_Martin-2020-NPR", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Semmelrath-2022-IRS", "field_id": "supervisor", "ordernum": 2 }, { "publ_id": "tatzgern-2020-sst", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1650", "__class": "Author" } ], "articleno": "48", "date_from": "2024-06-26", "date_to": "2024-06-28", "doi": "10.1145/3675373", "event": "High Performance Graphics", "issn": "2577-6193", "journal": "Proceedings of the ACM on Computer Graphics and Interactive Techniques", "lecturer": [ { "id": 1116, "drupal_id": 302, "orcid_id": "0000-0002-8166-3089", "website": "https://www.cg.tuwien.ac.at/staff/MarkusSchütz", "firstname": "Markus", "lastname": "Schütz", "searchname": "Markus Schütz", "is_teacher": false, "name": "Markus Schütz", "publications": [ "erler-2025-lidarscout", "goel-2024-rdr", "kroesl_x_card_2017", "Martinez-2015-TTB", "OTEPKA-2020-PPC", "schuetz_markus-2013-pra", "SCHUETZ-2014-RRLP", "SCHUETZ-2015-HQP", "SCHUETZ-2016-POT", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2019-PCC", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-DISS", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schuetz-mb", "TR 193-02-2019-4", "TR 193-2-2019-4", "unterguggenberger-2024-fropo" ], "publications_first": [], "project_leader": [ "d9691" ], "publication_field": [ { "publ_id": "BAUER-2024-PWG", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "BAUER-2025-PCW", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "ERLER-2017-HVR", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "FRAISS-2017-PCU", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "gersthofer_2017_COP", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "goel-2024-rdr", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "ioannis-2026-sro", "field_id": 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physics of light.", "abstract": "The rendering of 3D models and scenes has been a major, long-standing challenge in computer graphics that can be divided into two major subfields. Real-time rendering refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of physically based rendering focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. 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"koenigsberger-2024-msu", "koeppel-2016-baa", "Koeppl-2023-DLO", "koessler-2013-BA", "Kogelnig_Philip-2008-OGC", "kohlhas_jakob-2023-pra", "Kollmann-2015-DoF", "komon-2026-rso", "Komon2022", "konrad-2020-baa", "Kovacs_2017", "kovacs-2023-ttm", "kovacs-2025-pf", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "KREUZER-2014-DPA", "KREUZER-2015-DPA", "kreuzer-2016-isf", "KREUZER-2017-PBF", "kristmann-2022-occ", "kristmann-2023-vkl", "KRISTMANN-24-JPG", "kristmann-thesis", "Kroesl_2020_11_09", "Kroesl_Katharina_2016_PPT", "kroesl-2012-rtpm", "kroesl-2017-LiteMaker", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-MoD", "KROESL-2020-SVI", "kroesl-2020-XREye", "kubicek-2024-baa", "KUE11", "kuehtreiber-2010-ikph", "Kugler-2021", "kusternig-2009-rtr", "laager_florian-2013-camr", "laager_florian-2014-daa", "labschuetz-2010-bms", "labschuetz-2011-rsr", "Lan25", "landauer-2022-kido", "lang_jakob-2022-baa", "Langer_2013_ExactGeom", "lazarevic-tci", 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"SCHUETZ-2016-POT", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-DISS", "SCHUETZ-2021-PCC", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schulz-faf", "schwaerzler_2018_phd", "schwaerzler-2009-ass", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "SCHWAERZLER-2017-SBGM", "schwarz-2024-m2m", "Schwengerer_Mathias-2022-BGL", "seczer-2025-vrs", "seidemann-bachelor-2013", "seisenbacher-cyclesafely", "Selig_2005_WRO", "Selig-2007-VegAnim", "Semmelrath-2022-IRS", "seyr-2025-lbt", "SIETZEN-2017-BBO", "silvana_2014", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "Spechtenhauser_Florian_2013_SIU", "spelitz_stefan-2012-CDTFMR", "sperl-2013-BA", "Sperl-praktikum-2016", "spielmann-2006-ner", "spitaler-2015-pbi", "spitaler-afr-2011", "SSMW09", "stappen_SteFAS", "stappen-2019-vrs", "starnberger-cli", "stauss-2025-gfd", "steiner_2016_isad", "steiner_2016_isad", "STEINER-2006-SVC", "steiner-2013-BS", "steiner-2014-da", "steinheber-2024-oto", "steinkellner-2022-dll", "steinkellner-2024-dll", "STEINLECHNER-2019-APS", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter", "Stingl_2011_RHS", "STINGL-2009-RHS", "Stoll2020", "STREICHER-2022-DSLS", "Streicher-bachelor-2013", "STU-SR-25", "sturl_andreas-caflm", "STURN-2013-LGI", "STURN-2013-LSI", "Sturn-2013-ST", "sturn-thesis", "stutter_david-2012-kft", "subtil-2006-disp", "SUNDSTEDT-2008-ASF", "sundstedt-2013-vag", "szabo_2013_ssrr", "Tanzmeister_2011_I3D", "tatzgern-2020-sst", "telaar_sina-2026-baa", "Thann_2019_01", "themmer-2018-fbx", "thurner-2019-ani", "TK_2011", "tobler02_amrmg", "tobler02_mbpls", "tobler97_hsdasr", "TOMASCHITZ-2020-EP", "TOROMANOFF-2005-ASA", "TR 193-02-2019-4", "TR-186-2-02-04", "TR-186-2-05-05", "TR-186-2-06-02", "TR-186-2-07-01", "TR-186-2-07-09", "TR-186-2-08-09", 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"WIMMER-2016-FUTURIS", "WIMMER-2016-HARVEST4D", "WIMMER-2019-CGSG", "WIMMER-2020-ASG", "wimmer-2022-acd", "wimmer-2023-acd", "Win25", "WINKLER-2013-AMO", "Winkler-2017", "WINKLER-2019-PDG", "winklhofer_christoph-2013-RRMR", "winklmueller-aso", "withalm_brigitte-2022-baa", "Woerister_2012_ACS", "wolffhardt-2026-prj", "wonka-2000-VisP", "Wonka-2001-Ins", "Wonka-2001-IV", "Wonka-2003-Ins", "WONKA-2006-GVS", "x-mas-2013", "xmas-2025", "yoo-chaeran-2025-pr", "zapotocky_2013_ma", "ZAU14", "zeilinger_matthias-2020-baa", "Zezulka_Matthias-2023-MatLabOptInterface", "Zezulka-2024-FTS", "Zezulka-2025-NRL", "Zezulka-2026-FGTS", "Zezulka-2026-GridThermalSim", "zhang_le-2010-IGA", "zhang-thesis", "ZL_2011_IVIG", "zotti-2001-dip", "zotti-2003-ash", "zotti-2005-lum", "Zotti-2005-vis", "zotti-2006-dgm", "zotti-2006-pla", "zotti-2007-eg", "zotti-2007-hdr", "zotti-2007-PhD", "zotti-2007-wscg", "ZOTTI-2016-VAA", "ZOTTI-2017-BM", "ZOTTI-2017-TSP", "zsolnai-2018-gms", "zsolnai-feher-thesis-2019", "zsolnai-ist-invited-2014", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=rend", "__class": "Workgroup" }, { "id": "d9275", "workgroup_id": "vis", "drupal_id": 9275, "drupal_path": "/research/projects/IVILPC", "name": "Instant Visualization and Interaction for Large Point Clouds", "name_de": null, "short_title": "IVILPC", "website": null, "status": "active", "short_abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

\r\n", "abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

\r\n", "start_date": "2023-07-02", "end_date": "2026-07-01", "leader_id": 166, "logo": { "name": "logo.png", "path": "project:d9275", "type": "image/png", "size": 268858, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/d9275/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [], "research_areas": [ "Geometry", "Rendering", "VR" ], "publications": [ "erler-2025-lidarscout", "goel-2024-rdr", "grammatikaki-2026-treeon", "kerbl-2024-ah3", "papantonakis-2024-rmf", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "ulschmid-2024-reo", "ulschmid-2025-apc", "unterguggenberger-2024-fropo", "voglreiter-2023-tro" ], "url": "https://www.cg.tuwien.ac.at/research/projects/IVILPC", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/goel-2024-rdr/", "__class": "Publication" }, { "id": "kerbl-2024-ah3", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/220026", "title": "A Hierarchical 3D Gaussian Representation for Real-Time Rendering of Very Large Datasets", "date": "2024-07-19", "abstract": "Novel view synthesis has seen major advances in recent years, with 3D Gaussian splatting offering an excellent level of visual quality, fast training and real-time rendering. However, the resources needed for training and rendering inevitably limit the size of the captured scenes that can be represented with good visual quality. We introduce a hierarchy of 3D Gaussians that preserves visual quality for very large scenes, while offering an efficient Level-of-Detail (LOD) solution for efficient rendering of distant content with effective level selection and smooth transitions between levels. We introduce a divide-and-conquer approach that allows us to train very large scenes in independent chunks. We consolidate the chunks into a hierarchy that can be optimized to further improve visual quality of Gaussians merged into intermediate nodes. Very large captures typically have sparse coverage of the scene, presenting many challenges to the original 3D Gaussian splatting training method; we adapt and regularize training to account for these issues. We present a complete solution, that enables real-time rendering of very large scenes and can adapt to available resources thanks to our LOD method. We show results for captured scenes with up to tens of thousands of images with a simple and affordable rig, covering trajectories of up to several kilometers and lasting up to one hour.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "date_from,date_to,event,lecturer,location", "repositum_presentation_id": null, "authors": [ { "id": 1650, "drupal_id": 1494, "orcid_id": "0000-0002-5168-8648", "website": "https://www.cg.tuwien.ac.at/staff/BernhardKerbl", "firstname": "Bernhard", "lastname": "Kerbl", "searchname": "Bernhard Kerbl", "is_teacher": false, "name": "Bernhard Kerbl", "publications": [ "cardoso-2022-rtpercept", "celarek-2022-gmcn", "celarek-2025-d3g", "goel-2024-rdr", "hladky-2022-QS", "kenzel_michael_2021_cuda", "kerbl_2019_planet_poster", "kerbl_2021_hdg", "kerbl-2020-improvencoding", "kerbl-2022-cuda", "kerbl-2022-trienc", "kerbl-2024-ah3", "murturi_PGG", "papantonakis-2024-rmf", "roth_vdi", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", 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"__class": "Author" }, { "id": 5373, "drupal_id": null, "orcid_id": "0009-0003-5343-2528", "website": null, "firstname": "Alexandre", "lastname": "Lanvin", "searchname": "Alexandre Lanvin", "is_teacher": false, "name": "Alexandre Lanvin", "publications": [ "kerbl-2024-ah3", "papantonakis-2024-rmf" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5373", "__class": "Author" }, { "id": 5503, "drupal_id": null, "orcid_id": "0000-0002-9254-4819", "website": null, "firstname": "G.", "lastname": "Drettakis", "searchname": "G. 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Real-time rendering refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of physically based rendering focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. Another aspect of our research work revolves around tools that facilitate the work of content creators.", "website": "https://www.cg.tuwien.ac.at/research/area/Rendering", "teaser": { "name": "teaser.png", "path": "research_area:Rendering", "type": "image/png", "size": 5244928, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Rendering/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "2011scherzerE", "2018_Mautner_Praktikum", "ABG25", "Adorjan-2015", "agyemang-2021-bsdfproxyppg", "Ams25", "antes-g", "arikan-2014-pcvis", "arikan-2015-dmrt", "Artusi-2003-Del", "ASCHL-2022-OTV", "Auzinger_2012_AAA", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", "Auzinger_2014_DCGI", "Auzinger_2014_UJA", "Auzinger-2015-IST", "bagar2010", "balvan-g", "Bauer_Dominik_2018_VR", "BAUER-2024-PWG", "BAUER-2025-PCW", "bernhard-2011-bmtf", 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Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

\r\n", "abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

\r\n", "start_date": "2023-07-02", "end_date": "2026-07-01", "leader_id": 166, "logo": { "name": "logo.png", "path": "project:d9275", "type": "image/png", "size": 268858, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/d9275/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [], "research_areas": [ "Geometry", "Rendering", "VR" ], "publications": [ "erler-2025-lidarscout", "goel-2024-rdr", "grammatikaki-2026-treeon", "kerbl-2024-ah3", "papantonakis-2024-rmf", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "ulschmid-2024-reo", "ulschmid-2025-apc", "unterguggenberger-2024-fropo", "voglreiter-2023-tro" ], "url": "https://www.cg.tuwien.ac.at/research/projects/IVILPC", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/kerbl-2024-ah3/", "__class": "Publication" }, { "id": "SCHUETZ-2024-SIMLOD", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/208716", "title": "SimLOD: Simultaneous LOD Generation and Rendering for Point Clouds", "date": "2024-05-13", "abstract": "LOD construction is typically implemented as a preprocessing step that requires users to wait before they are able to view the results in real time. We propose an incremental LOD generation approach for point clouds that allows us to simultaneously load points from disk, update an octree-based level-of-detail representation, and render the intermediate results in real time while additional points are still being loaded from disk. LOD construction and rendering are both implemented in CUDA and share the GPU’s processing power, but each incremental update is lightweight enough to leave enough time to maintain real-time frame rates. Our approach is able to stream points from an SSD and update the octree on the GPU at rates of up to 580 million points per second (~9.3GB/s) on an RTX 4090 and a PCIe 5.0 SSD. Depending on the data set, our approach spends an average of about 1 to 2 ms to incrementally insert 1 million points into the octree, allowing us to insert several million points per frame into the LOD structure and render the intermediate results within the same frame.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Rendered Point Cloud to the left and points/voxels colored by the containing octree node to the right.", "filetitle": "SimLOD", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1911, "image_height": 1072, "name": "SCHUETZ-2024-SIMLOD-SimLOD.jpg", "type": "image/jpeg", "size": 323598, "path": "Publication:SCHUETZ-2024-SIMLOD", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/SCHUETZ-2024-SIMLOD/SCHUETZ-2024-SIMLOD-SimLOD.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/SCHUETZ-2024-SIMLOD/SCHUETZ-2024-SIMLOD-SimLOD:thumb{{size}}.png" }, "sync_repositum_override": "event", "repositum_presentation_id": null, "authors": [ { "id": 1116, "drupal_id": 302, "orcid_id": "0000-0002-8166-3089", "website": "https://www.cg.tuwien.ac.at/staff/MarkusSchütz", "firstname": "Markus", "lastname": "Schütz", "searchname": "Markus Schütz", "is_teacher": false, "name": "Markus Schütz", "publications": [ "erler-2025-lidarscout", "goel-2024-rdr", "kroesl_x_card_2017", "Martinez-2015-TTB", "OTEPKA-2020-PPC", "schuetz_markus-2013-pra", "SCHUETZ-2014-RRLP", "SCHUETZ-2015-HQP", "SCHUETZ-2016-POT", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2019-PCC", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-DISS", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schuetz-mb", "TR 193-02-2019-4", "TR 193-2-2019-4", 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Real-time rendering refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of physically based rendering focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. 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"ROEGNER-2015-IBR", "roth_2021_vdst", "roth_vdi", "roth-2023-vlk", "rumpelnik_martin_2020_PRM", "Rumpelnik_Martin-2020-NPR", "rumpler_2019_PPC", "Rumpler-2019-PPC", "RUMPLER-2021-VOGL", "SAKAI-2015-EAPI", "sakai-2021-eif", "sakai-2024-asa", "sakai-2025-stater", "sakai-thesis", "schedl-2012-dof", "schedl-2013-gP4", "SCHEIBLAUER-2015-WFC", "scherzer_2010a", "Scherzer-2007-PCS", "SCHERZER-2008-FSR", "scherzer-2009-isvc", "SCHERZER-2012-TCM", "scherzer-eg2010", "scherzer-thesis", "scherzer2010b", "scherzer2010d", "scherzer2010e", "scherzer2011c", "scherzer2011d", "SCHOBER-2006-IVSA", "SCHUETZ-2015-HQP", "SCHUETZ-2016-POT", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2019-PCC", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-DISS", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schuetz-mb", "schwaerzler_2018_phd", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "Schwengerer_Mathias-2022-BGL", 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"werdermann-va", "WESSNER-2019-PCW", "wiesinger_2020_odpr", "wiesinger-2023-gcg", "Wilkie-2001-Ori", "Wilkie-2004-AMS", "wilkie-2006-dfs", "wilkie-2009-cc", "Wimmer-1999-FWIa", "Wimmer-1999-FWIb", "Wimmer-2001-Poi", "Wimmer-2003-RTE", "Wimmer-2004-LSPM", "Wimmer-2005-HOQ", "WIMMER-2006-PSM", "WIMMER-2006-SIV", "WIMMER-2007-GAR", "WIMMER-2007-RTR", "WIMMER-2008-ART", "WIMMER-2008-CAR", "WIMMER-2008-PVR", "WIMMER-2009-ARTR", "WIMMER-2009-ARTR2", "WIMMER-2009-ARTR3", "WIMMER-2009-CSR", "WIMMER-2009-VCCG", "WIMMER-2016-HARVEST4D", "WIMMER-2019-CGSG", "WIMMER-2020-ASG", "Win25", "winklmueller-2025-ims", "wonka-2000-VisP", "Wonka-2001-Ins", "WONKA-2006-GVS", "x-mas-2013", "zeilinger_matthias-2020-baa", "Zezulka_Matthias-2023-MatLabOptInterface", "Zezulka-2024-FTS", "Zezulka-2025-NRL", "Zezulka-2026-FGTS", "zotti-2005-lum", "zotti-2006-pla", "zotti-2007-PhD", "zotti-2007-wscg", "ZOTTI-2016-VAA", "ZOTTI-2017-BM", "ZOTTI-2017-TSP", "zsolnai-2018-gms", "zsolnai-feher-thesis-2019", "zsolnai-ist-invited-2014", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "projects": [ "3DSpatialization", "d9259", "d9275", "d9555", "Desiree", "EVOCATION", "GameTools", "GPV", "Harvest4D", "Mofa", "OpenData", "PathSpace", "REPLICATE", "RESHADE", "Scanopy", "TERAPOINTS", "Treelumination" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Rendering", "__class": "ResearchArea" } ], "keywords": [ "LOD", "real-time rendering", "Point Cloud Rendering", "rasterization", "Octree" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "SCHUETZ-2024-SIMLOD-paper.pdf", "type": "application/pdf", "size": 5928589, "path": "Publication:SCHUETZ-2024-SIMLOD", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/SCHUETZ-2024-SIMLOD/SCHUETZ-2024-SIMLOD-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/SCHUETZ-2024-SIMLOD/SCHUETZ-2024-SIMLOD-paper:thumb{{size}}.png" }, { "description": "Rendered Point Cloud to the left and points/voxels colored by the containing octree node to the right.", "filetitle": "SimLOD", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1911, "image_height": 1072, "name": "SCHUETZ-2024-SIMLOD-SimLOD.jpg", "type": "image/jpeg", "size": 323598, "path": "Publication:SCHUETZ-2024-SIMLOD", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/SCHUETZ-2024-SIMLOD/SCHUETZ-2024-SIMLOD-SimLOD.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/SCHUETZ-2024-SIMLOD/SCHUETZ-2024-SIMLOD-SimLOD:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "d9275", "workgroup_id": "vis", "drupal_id": 9275, "drupal_path": "/research/projects/IVILPC", "name": "Instant Visualization and Interaction for Large Point Clouds", "name_de": null, "short_title": "IVILPC", "website": null, "status": "active", "short_abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

\r\n", "abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

\r\n", "start_date": "2023-07-02", "end_date": "2026-07-01", "leader_id": 166, "logo": { "name": "logo.png", "path": "project:d9275", "type": "image/png", "size": 268858, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/d9275/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [], "research_areas": [ "Geometry", "Rendering", "VR" ], "publications": [ "erler-2025-lidarscout", "goel-2024-rdr", "grammatikaki-2026-treeon", "kerbl-2024-ah3", "papantonakis-2024-rmf", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "ulschmid-2024-reo", "ulschmid-2025-apc", "unterguggenberger-2024-fropo", "voglreiter-2023-tro" ], "url": "https://www.cg.tuwien.ac.at/research/projects/IVILPC", "__class": "Project" }, { "id": "d4386", "workgroup_id": "rend", "drupal_id": 4386, "drupal_path": "/research/projects/LargeClouds2BIM", "name": "Efficient workflow transforming large 3D point clouds to Building Information Models with user-assisted automatization", "name_de": "Efficient workflow transforming large 3D point clouds to Building Information Models with user-assisted automatization", "short_title": "LargeClouds2BIM", "website": null, "status": "active", "short_abstract": null, "abstract": null, "start_date": "2020-12-01", "end_date": "2022-11-30", "leader_id": 193, "logo": null, "funding_organisations": [], "research_areas": [], "publications": [ "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD" ], "url": "https://www.cg.tuwien.ac.at/research/projects/LargeClouds2BIM", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/SCHUETZ-2024-SIMLOD/", "__class": "Publication" }, { "id": "papantonakis-2024-rmf", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/198651", "title": "Reducing the Memory Footprint of 3D Gaussian Splatting", "date": "2024-05-13", "abstract": "3D Gaussian splatting provides excellent visual quality for novel view synthesis, with fast training and realtime rendering; unfortunately, the memory requirements of this method for storing and transmission are unreasonably high. We first analyze the reasons for this, identifying three main areas where storage can be reduced: the number of 3D Gaussian primitives used to represent a scene, the number of coefficients for the spherical harmonics used to represent directional radiance, and the precision required to store Gaussian primitive attributes. We present a solution to each of these issues. First, we propose an efficient, resolution-aware primitive pruning approach, reducing the primitive count by half. Second, we introduce an adaptive adjustment method to choose the number of coefficients used to represent directional radiance for each Gaussian primitive, and finally a codebook-based quantization method, together with a half-float representation for further memory reduction. Taken together, these three components result in a x27 reduction in overall size on disk on the standard datasets we tested, along with a x1.7 speedup in rendering speed. We demonstrate our method on standard datasets and show how our solution results in significantly reduced download times when using the method on a mobile device (see Fig. 1).", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "projects", "repositum_presentation_id": null, "authors": [ { "id": 5371, "drupal_id": null, "orcid_id": "0009-0009-5058-1249", "website": null, "firstname": "Panagiotis", "lastname": "Papantonakis", "searchname": "Panagiotis Papantonakis", "is_teacher": false, "name": "Panagiotis Papantonakis", "publications": [ "papantonakis-2024-rmf" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5371", "__class": "Author" }, { "id": 5372, "drupal_id": null, "orcid_id": "0009-0002-5829-2192", "website": null, "firstname": "Georgios", "lastname": "Kopanas", "searchname": "Georgios Kopanas", "is_teacher": false, "name": 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"name_de": null, "short_title": "IVILPC", "website": null, "status": "active", "short_abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

\r\n", "abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

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"MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "mayer_2011_cipa", "mayer_luiz-2026-baa", "MAYER-2010-MTX", "Mayer-2010-VT", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "MAYRHAUSER-2016-SCA", "mazza-2012-bakk", "Meier_2024_WIALT", "Meier_2024_WIALT", "MeierStauffer-2013-iihf", "metzger-2024-smv", "micu_2025-prj", "miklautsch_florian-baa", "MOELLINGER-2010-SD", "MORARU-2014-CPD", "mortezapoor-2022-photogrammabot", "Mortezapoor2021ssc", "Muehlbacher_2012_RRM", "Muehlbacher_2012_RTR", "MuehlbacherArbesser-2009-LMDLightcuts", "MUEHLBERGER-2010-AFSM", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2012_aachen", "musialski_2012_fice", "musialski_2016_sosp", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-prag", "musialski-2013-surcgf", "musialski-2015-ista", "musialski-2015-pixel", "musialski-2015-souos", "musialski-2015-vrvis", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "Neum03CAMR", "Neum04GCM", "neumann-2004-aip", "Neumann-2004-HOB", "neumann-2004-ipm", "neumann-2006-gamma", "neumann-sfd", "Niederreiter_2011_SM", "NIEDERREITER-2010-SIM", "NK_2011", "novak_martin-2018-baa", "Nuernberg-2011-CBO", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "ohrhallinger-stefan-2012-the", "OPPITZ-2017-3DM", "oppitz-2023-ais", "OPPTIZ-2018-IVRL", "OTEPKA-2020-PPC", "ott-rgi", "ott-va", "Pajer-2006-tmcg", "pakkanen-2026-prj", "panfili-2019-VAVR", "panfili-2021-myop", "pangerl_2013_GPD", "papantonakis-2024-rmf", "parakkat-2024-ballmerge", "parakkat-2024-ballmerge", "PARZER-2010-STELL", "PB-VRVis-2018-005", "pegrisch_2018_uvs", 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"reznicek-2020-fpgaray", "richter-2020-ani", "riegler_2020_framework", "roch-2007-rtt", "Roch2006", "Roegner_RHF_2010", "ROEGNER-2014-TUI", "ROEGNER-2015-IBR", "ROESSLER-2012-OGLES", "roth_2021_vdst", "roth_vdi", "roth-2023-vlk", "rozanics-lsf", "rubik_michael-2022-baa", "Rudolf_06_IDM", "rumpelnik_martin_2020_PRM", "rumpelnik_martin_2020_PRM", "Rumpelnik_Martin-2020-NPR", "rumpelnik-2022-vlk", "rumpler_2019_PPC", "Rumpler-2019-PPC", "RUMPLER-2021-VOGL", "rumpler-2023-dcmcm", "S05", "SABADELLO-2006-HEG", "sakai_2013", "SAKAI-2015-EAPI", "sakai-2021-eif", "sakai-2024-asa", "sakai-2025-stater", "sakai-thesis", "santos-2017-dacge", "sari2008mt", "SATZER-2008", "schaffarz_2018-pra", "scharl-master-thesis", "schartmueller_2018_baa", "schaukowitsch-2013-fls", "SCHAUKOWITSCH-2015-REMOTE", "SCHAUKOWITSCH-2015-STELL", "schedl-2012-dof", "schedl-2013-gP4", "schedl-thesis", "schefcik_juergen_2015_baa", "Scheiblauer-2006-DA", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "SCHEIBLAUER-2015-WFC", "scheiblauer-thesis", "scheiblauer-thesis", "scherzer_2010a", "Scherzer-2007-PCS", "SCHERZER-2008-FSR", "scherzer-2009-isvc", "SCHERZER-2012-TCM", "scherzer-eg2010", "scherzer-thesis", "scherzer2010b", "scherzer2010d", "scherzer2010e", "scherzer2011c", "scherzer2011d", "schmid_andreas_2013-prj", "schneider-sturm-2026-mia", "schober_florian_2012_aspm", "schoerkhuber_dominik-2016-baa", "scholz_2017_bac", "schrammel_sebastian_baa", "schuetz_markus-2013-pra", "SCHUETZ-2014-RRLP", "SCHUETZ-2015-HQP", "SCHUETZ-2016-POT", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-DISS", "SCHUETZ-2021-PCC", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schulz-faf", "schwaerzler_2018_phd", "schwaerzler-2009-ass", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "SCHWAERZLER-2017-SBGM", "schwarz-2024-m2m", "Schwengerer_Mathias-2022-BGL", "seczer-2025-vrs", "seidemann-bachelor-2013", "seisenbacher-cyclesafely", "Selig_2005_WRO", "Selig-2007-VegAnim", "Semmelrath-2022-IRS", "seyr-2025-lbt", "SIETZEN-2017-BBO", "silvana_2014", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "Spechtenhauser_Florian_2013_SIU", "spelitz_stefan-2012-CDTFMR", "sperl-2013-BA", "Sperl-praktikum-2016", "spielmann-2006-ner", "spitaler-2015-pbi", "spitaler-afr-2011", "SSMW09", "stappen_SteFAS", "stappen-2019-vrs", "starnberger-cli", "stauss-2025-gfd", "steiner_2016_isad", "steiner_2016_isad", "STEINER-2006-SVC", "steiner-2013-BS", "steiner-2014-da", "steinheber-2024-oto", "steinkellner-2022-dll", "steinkellner-2024-dll", "STEINLECHNER-2019-APS", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter", "Stingl_2011_RHS", "STINGL-2009-RHS", "Stoll2020", "STREICHER-2022-DSLS", "Streicher-bachelor-2013", "STU-SR-25", "sturl_andreas-caflm", "STURN-2013-LGI", "STURN-2013-LSI", "Sturn-2013-ST", "sturn-thesis", "stutter_david-2012-kft", "subtil-2006-disp", "SUNDSTEDT-2008-ASF", "sundstedt-2013-vag", "szabo_2013_ssrr", "Tanzmeister_2011_I3D", "tatzgern-2020-sst", "telaar_sina-2026-baa", "Thann_2019_01", "themmer-2018-fbx", "thurner-2019-ani", "TK_2011", "tobler02_amrmg", "tobler02_mbpls", "tobler97_hsdasr", "TOMASCHITZ-2020-EP", "TOROMANOFF-2005-ASA", "TR 193-02-2019-4", "TR-186-2-02-04", "TR-186-2-05-05", "TR-186-2-06-02", "TR-186-2-07-01", "TR-186-2-07-09", "TR-186-2-08-09", "TR-186-2-12-01", "Tragust-2012-GMHPC", "Tragust-2014-master-thesis", "traxler-1997-TRA", "trenkwalder-2008-landscape", "trenkwalder-2013-ma", "trenovatz-lpd", "trumpf_stefan_2012", "Tucek_2018", "Tucek_Tom-2016-aai", "tumpach_barbara-pra", "ulschmid-2024-reo", "ulschmid-2025-apc", "ulschmid-phdthesis", "unterguggenberger-2010-cmph", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2023-vaw", "unterguggenberger-2024-fropo", "unterguggenberger-phdthesis", "VASCO-2019-EVR", "vasiljevic-gpc", "VASILJEVS-2018-PMPL", "vis-foa", "VOELKL-2013-RTRS", "voglreiter-2023-tro", "Voglsam_2012_RTR", "Voglsam_2013_RRT", "wagentristl_stefan-2026-baa", "wagner-2024-par", "wallner_2008_ltosd", "WALLNER-2010-CSSAO", "wallner-2015-InfoTheoryPlay", "wallner-2015-ModelingRoutinization", "Wang-2016-BAC", "wang-sifuentes-2018-cgbase", "weber_2008_sh", "WEBER-2012-MIC", "WEBER-2015-PRA", "WEBER-2015-PRA1", "weidlich_2009_REL", "weidlich-2009-dispersion", "weidlich-2009-thesis", "weiner-2010-eud", "weinzierl_2012_iism", "weinzierl_heigl-2017-wh14", "Wenigwieser2007", "werdermann-va", "WESSNER-2019-PCW", "WEYDEMANN-2014-PIC", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "weydemann-praktikum-2016", "wieser-2019-ani", "wiesinger_2020_odpr", "wiesinger_2020_odpr", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wiesinger-2023-gcg", "wildt-tci", "Wilkie-2001-Ori", "Wilkie-2004-AMS", "wilkie-2006-dfs", "wilkie-2009-cc", "Wimmer-1999-FWIa", "Wimmer-1999-FWIb", "Wimmer-2001-PBI", "Wimmer-2001-Poi", "Wimmer-2003-RTE", "Wimmer-2004-LSPM", "Wimmer-2005-HOQ", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2006-PSM", "WIMMER-2006-SIV", "WIMMER-2007-GAR", "WIMMER-2007-RTR", "WIMMER-2008-ART", "WIMMER-2008-CAR", "WIMMER-2008-PVR", "WIMMER-2009-ARTR", "WIMMER-2009-ARTR2", "WIMMER-2009-ARTR3", "WIMMER-2009-CSR", "WIMMER-2009-ITC", "WIMMER-2009-VCCG", "WIMMER-2014-DWNT", "WIMMER-2015-CGFC", "WIMMER-2015-CGMC", "WIMMER-2016-FUTURIS", "WIMMER-2016-HARVEST4D", "WIMMER-2019-CGSG", "WIMMER-2020-ASG", "wimmer-2022-acd", "wimmer-2023-acd", "Win25", "WINKLER-2013-AMO", "Winkler-2017", "WINKLER-2019-PDG", "winklhofer_christoph-2013-RRMR", "winklmueller-aso", "withalm_brigitte-2022-baa", "Woerister_2012_ACS", "wolffhardt-2026-prj", "wonka-2000-VisP", "Wonka-2001-Ins", "Wonka-2001-IV", "Wonka-2003-Ins", "WONKA-2006-GVS", "x-mas-2013", "xmas-2025", "yoo-chaeran-2025-pr", "zapotocky_2013_ma", "ZAU14", "zeilinger_matthias-2020-baa", "Zezulka_Matthias-2023-MatLabOptInterface", "Zezulka-2024-FTS", "Zezulka-2025-NRL", "Zezulka-2026-FGTS", "Zezulka-2026-GridThermalSim", "zhang_le-2010-IGA", "zhang-thesis", "ZL_2011_IVIG", "zotti-2001-dip", "zotti-2003-ash", "zotti-2005-lum", "Zotti-2005-vis", "zotti-2006-dgm", "zotti-2006-pla", "zotti-2007-eg", "zotti-2007-hdr", "zotti-2007-PhD", "zotti-2007-wscg", "ZOTTI-2016-VAA", "ZOTTI-2017-BM", "ZOTTI-2017-TSP", "zsolnai-2018-gms", "zsolnai-feher-thesis-2019", "zsolnai-ist-invited-2014", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=rend", "__class": "Workgroup" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/papantonakis-2024-rmf/", "__class": "Publication" }, { "id": "unterguggenberger-2024-fropo", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/199275", "title": "Fast Rendering of Parametric Objects on Modern GPUs", "date": "2024-05", "abstract": "Parametric functions are an extremely efficient representation for 3D geometry, capable of compactly modelling highly complex objects. Once specified, parametric 3D objects allow for visualization at arbitrary levels of detail, at no additional memory cost, limited only by the amount of evaluated samples. However, mapping the sample evaluation to the hardware rendering pipelines of modern graphics processing units (GPUs) is not trivial. This has given rise to several specialized solutions, each targeting interactive rendering of a constrained set of parametric functions. In this paper, we propose a general method for efficient rendering of parametrically defined 3D objects. Our solution is carefully designed around modern hardware architecture. Our method adaptively analyzes, allocates and evaluates parametric function samples to produce high-quality renderings. Geometric precision can be modulated from few pixels down to sub-pixel level, enabling real-time frame rates of several 100 frames per second (FPS) for various parametric functions. We propose a dedicated level-of-detail (LOD) stage, which outputs patches of similar geometric detail to a subsequent rendering stage that uses either a hardware tessellation-based approach or performs point-based softare rasterization. Our method requires neither preprocessing nor caching, and the proposed LOD mechanism is fast enough to run each frame. Hence, our approach also lends itself to animated parametric objects. We demonstrate the benefits of our method over a state-of-the-art spherical harmonics (SH) glyph rendering method, while showing its flexibility on a range of other demanding shapes.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Teaser image, different parametric objects", "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 1440, "image_height": 1364, "name": "unterguggenberger-2024-fropo-image.png", "type": "image/png", "size": 2235242, "path": "Publication:unterguggenberger-2024-fropo", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/unterguggenberger-2024-fropo/unterguggenberger-2024-fropo-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/unterguggenberger-2024-fropo/unterguggenberger-2024-fropo-image:thumb{{size}}.png" }, "sync_repositum_override": "date,projects", "repositum_presentation_id": null, "authors": [ { "id": 848, "drupal_id": 1219, "orcid_id": "0000-0001-6453-8158", "website": "https://www.cg.tuwien.ac.at/staff/JohannesUnterguggenberger", "firstname": "Johannes", "lastname": "Unterguggenberger", "searchname": "Johannes Unterguggenberger", "is_teacher": false, "name": "Johannes Unterguggenberger", "publications": [ "stappen_SteFAS", "unterguggenberger-2010-cmph", "unterguggenberger-2016-realmar", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2023-ait", "unterguggenberger-2023-vaw", "unterguggenberger-2024-fropo", "unterguggenberger-phdthesis", "xmas-2023" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "brandmair-2024-bind", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "brandmair-2024-m2m", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "brandmair-2024-rust", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "brandmair-2025-rub", 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Real-time rendering refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of physically based rendering focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. 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"zsolnai-ist-invited-2014", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "projects": [ "3DSpatialization", "d9259", "d9275", "d9555", "Desiree", "EVOCATION", "GameTools", "GPV", "Harvest4D", "Mofa", "OpenData", "PathSpace", "REPLICATE", "RESHADE", "Scanopy", "TERAPOINTS", "Treelumination" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Rendering", "__class": "ResearchArea" } ], "keywords": [ "Tessellation Shaders", "Point-Based Rendering", "Parametric Objects", "Fast Rendering", "Modern GPUs" ], "weblinks": [ { "href": "https://github.com/cg-tuwien/FastRenderingOfParametricObjects", "caption": "FastRenderingOfParametricObjects", "description": "Source Code on GitHub", "main_file": 0 } ], "files": [ { "description": "Teaser image, different parametric objects", "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 1440, "image_height": 1364, "name": "unterguggenberger-2024-fropo-image.png", 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"https://www.cg.tuwien.ac.at/research/publications/2024/unterguggenberger-2024-fropo/unterguggenberger-2024-fropo-paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "d9275", "workgroup_id": "vis", "drupal_id": 9275, "drupal_path": "/research/projects/IVILPC", "name": "Instant Visualization and Interaction for Large Point Clouds", "name_de": null, "short_title": "IVILPC", "website": null, "status": "active", "short_abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

\r\n", "abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

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"birsak-thesis", "birsak-thesis", "Birsak2018-SA", "Bittner-2001-Vis", "Bittner-2003-Vis", "Bittner-2004-CHC", "bittner-2005-egsr", "bittner-2005-egsr", "BITTNER-2009-AGVS", "BITTNER-2009-GEFOC", "bittner-2011-scc", "bodzenta-2026-baa", "Bogner-2008-MTh", "boindl_2013", "BOKSANSKY-2019-RTS", "BORZA-2012-Stellarium", "brandmair-2024-bind", "brandmair-2024-rust", "brandmair-2025-rub", "Brandorff_06_PON", "Brandorff_06_SKIN", "brenner_simon-2013-ba", "brugger-2020-tdp", "brugger-2020-tsdpbr", "brugger-2020-tsdpbr", "brunner_lukas_2022_ssb", "Brusi-2001-Opt", "CADIK-2006-IAQ", "CADIK-2008-EHD", "Calatrava_2013_GPGPUSOA", "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "cech-2023-taa", "celarek_adam-2012-rrmro", "celarek_adam-2019-qelta", "celarek_adam-2019-qelta", "CELAREK-2017-QCL", "CELAREK-2017-QCL", "celarek-2022-gmcn", "celarek-2022-gmcn", "celarek-2022-gmcn", "celarek-thesis", "CHARALAMBOS-2007-HLOD", "charpenay-2013-PR", "charpenay-2014-sgn", "Che-2025", "CHIU-2008-PEN", "clemenz_2019_rosy_fields", "CORNEL-2010-VIS", "CORNEL-2014-AFRS", "CORNEL-2017-FRS", "CORNEL-2019-IVF", "csecsy-fcd", "darovskikh_leonid-2025-prj", "dataset", "dataset-cat", "dataset-chair", "dataset-dragon", "dataset-duck", "dataset-ferris-wheel", "dataset-penguin", "dataset-strauss", "dataset-tramway", "dataset-viennacity", "daubner-2007-HDR", "deak-a3", "deix-2008-rcp", "dellmour-2013-grs", "depner_dennis-2020-baa", "depner_dennis-2022-maa", "Derflinger-2024-RTTW", "Derflinger-2026-RTTW2", "Devlin-2002-STA", "dodik-2017-pcbpt", "Doerflinger-2016-CDV", "Dogangonul-2013-sparkGL", "druml-2010-PFL", "Druml-2013-3DrC", "dusberger-2010-msm", "ecormier-nocca-2025-sls", "eibens-2021-tsgpmg", "eibensteiner-2016-pmg", "eibensteiner-2021-pmcg", "eickmeyer-2027-tcd", "EISEMANN-2011-RTS", "EISEMANN-2012-ERT", "EISEMANN-2013-ERT", "elagrod_ahmed-baa", "Erhardt_2025_Scutes", "Erhardt_Seirlehner-2024-TamashiiIntegration", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "erler_philipp-2017-phd", "erler_philipp-2017-phd", "ERLER-2017-HVR", "erler-2020-p2s", "erler-2020-p2s", "erler-2020-p2s", "erler-2025-lidarscout", "ERNST-2010-IOOC", "ernst-2013-fif", "ESBERGER-2016-AHO", "ESCHNER-2019-GDT", "fan-2014-scfl", "fan-2014-scfl", "Fauster-06-st", "Felberbauer_2012_AG", "fiedler-2009-php", "fiedler-2022-vlk", "fink-2012-cg1", "fink-2013-cag", "fink-2013-gvp", "Fischer-2018-sssvr", "fitzinger_andreas-daa", "fizimayer-2007-art", "fleiss-2015-da", "forsythe-2016-ccm", "FRAISS-2017-PCU", "fraiss-2019-rtx", "FRAISS-2022-CGMM", "fraissl_niklas-2023-pra", "freude_2020_rs", "Freude_MSc", "FREUDE-2015-phd", "freude-2023-prh", "freude-2023-prh", "freude-2023-sem", "freude-2023-sem", "freude-2025-iso", "freude-2025-iso", "freude-2025-ras", "Fritz-2012", "fruehstueck-2008-gpu", "fuchs_peter-2024-baa", "fuericht_2025_prj", "fuericht_elias-2025-prj", "Fuericht-2026-FPD", "Fuerst_2014_BSc", "Fuerst-2009-dfr", "FUERST-2013-RTWS", "Fuerst-Bachelor-2013", "G_P_06_RFS", "GAHR-2013-AGM", "gamper_2008_or", "GAMPER-2018-OSG", "gamsjaeger-2022-proc", "gangl-2018-cgbase", "GANTNER-2018-ARO", "GANTNER-2019-CRS", "GEBHART-2008-AGV", "gersthofer_2017_COP", "gersthofer-2016-sosob", "geyer_lukas_2015_prj", "geyer_lukas-2014-bat", "geyer-2018-apbf", "giefing_juergen-2013-ba", "GIEGL-2006-QVS", "GIEGL-2007-FVS", "GIEGL-2007-QV1", "GIEGL-2007-UNP", "gilmutdinov-2022-aomlbwug", "glanz-2017-pbrcomparison", "goel-2024-rdr", "goetz_johann-cagmfp", "Goldmann_2011_GPU", "gramegna-rfr", "Grasberger_08_VV", "Grasberger_2008_ISR", "grasberger_2009_CSB", "GRELAUD-2009-EPA", "GRIESHOFER-2018-GOS", "Grisenti-2026-HSHPG", "grosse-2009-avp", "Grossfurtner-2023-paego", "grossmann-2016-baa", "gruber_horst-2019-baa", "Gruber2019", "Guerrero_Paul_2014_EPG", "guerrero-2008-dip", "guerrero-2008-sli", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "gurtler-2014-ssggm", "Gusenbauer_Matthias_2015_ANM", "Habel_07_xms", "Habel_08_SSH", "Habel_09_PGT", "Habel_09_PGT", "Habel_2007_IAG", "Habel_2007_RTT", "Habel_2009_PhD", "Habel_2012_PSP", "Habel_LSN_2011", "Habel_RAV_2010", "Habel-09-RAT", "Habel-09-THB", "Habel-2010-EIN", "hafner_christian-2013-oflow", "hafner-2015-eigf", "HAFNER-2015-FEM", "hafner-2015-onff", "halbritter-2024-m2m", "hamzic_ademir-baa", "hanko-2019-ani", "HANN_2022_IPT", "harisch-mvs", "Hartl_2006_OgC", "hasbay-2026-tfo", "hatzinger-2026-baa", "hauer_alex-2013-ba", "havran-2005-egsr", "havran-2005-sccg", "havran-2006-tut", "Hebart-2011-ColorAdjustment", "HECHER-2010-3DS", "hecher-2012-MH", "hecher-2014-MH", "HECHER-2017-HDY", "heinz-2019-psi", "heiss-rfr", "herzberger-2021-cmake", "hofer_kerstin-2023-sketch2model", "hoffer-toth-com", "holom_2025-prj", "Holzer-06-HDR", "Honic_2021", "hornacek-2010-evp", "horvath_imp", "houska-2020-IPGM", "HU-2017-ETM", "huber-2025-esl", "huerbe-2019-BA", "HUMMEL-2001-MSE", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2011-pmous", "ilcik-2013-cipmi", "ilcik-2013-pmsg", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ILCIK-phdthesis", "ilcikova-thesis", "intel2016", "ioannis-2026-sro", "Ishmukhametov_Denis_2011_EIN", "jafari-2023-avk", "jahrmann_klemens_KFR", "JAHRMANN-2013-IGR", "JAHRMANN-2015-GRASS", "JAHRMANN-2016-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-AIP", "jeschke-05-ARI", "jeschke-05-ISTAR", "jeschke-09-praguetalk", "jeschke-09-rendering", "jeschke-09-solver", "Jeschke-2002-LEM", "Jeschke-2002-LEMA", "Jeschke-2002-TDM", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "jeschke-2010-diff", "jeschke-2011-est", "jeschke-2011-esttalk", "jeschke-2011-talkPrague", "Jia-thesis", "Jimenez_SSS_2015", "jira_marcel-2024-baa", "JORDAKIEVA-2017-VFR", "KAFKA-2014-19MRD", "kaipel_nikolas-2025-baa", "kapferer_2021_advancing", "karampekios_anastasios-prj", "Kathi-2018-VRB", "kazda-tmd", "Keilman2022", "kendlbacher-2016", "kenzel_michael_2021_cuda", "kerbl_2019_planet_poster", "kerbl_2021_hdg", "kerbl-2020-improvencoding", "kerbl-2022-cuda", "kerbl-2022-trienc", "kimmersdorfer-2021-mzip", "kimmersdorfer-2024-vcpr", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "KLAUS-2020-PCC", "klein-2020-rtgi", "kment_2008_cc", "knecht_2013_RSM", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "Knecht_Schwaerzler_2008_ash", "knecht-2007-ao", "knecht-2009-MKN", "knecht-2009-TAS", "knecht-2011-CBCM", "knoetzl_alexander-2025-prj", "koch-2019-PR", "KOCH-2021-GVS", "KOCH-2021-GVSDA", "koenigsberger-2024-msu", "koeppel-2016-baa", "Koeppl-2023-DLO", "koessler-2013-BA", "Kogelnig_Philip-2008-OGC", "kohlhas_jakob-2023-pra", "Kollmann-2015-DoF", "komon-2026-rso", "Komon2022", "konrad-2020-baa", "Kovacs_2017", "kovacs-2023-ttm", "kovacs-2025-pf", "kozonits_marcel-2025-baa", "kralicek_sebastian_baa", "KREUZER-2014-DPA", "KREUZER-2015-DPA", "kreuzer-2016-isf", "KREUZER-2017-PBF", "kristmann-2022-occ", "kristmann-2023-vkl", "KRISTMANN-24-JPG", "kristmann-thesis", "Kroesl_2020_11_09", "Kroesl_Katharina_2016_PPT", "kroesl-2012-rtpm", "kroesl-2017-LiteMaker", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-MoD", "KROESL-2020-SVI", "kroesl-2020-XREye", "kubicek-2024-baa", "KUE11", "kuehtreiber-2010-ikph", "Kugler-2021", "kusternig-2009-rtr", "laager_florian-2013-camr", "laager_florian-2014-daa", "labschuetz-2010-bms", "labschuetz-2011-rsr", "Lan25", "landauer-2022-kido", "lang_jakob-2022-baa", "Langer_2013_ExactGeom", "lazarevic-tci", "LEHNINGER-2007-SSV", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer_2020-cag", "leimer_2020-cag", "leimer-2013-esopc", "leimer-2014-fsco", "leimer-2016-coan", "leimer-2016-rpe", "leimer-2018-sar", "leimer-2018-sar", "leimer-2023-ecd", "LEOPOLD-2017-ALG", "leopold-2019-vox", "leutschacher_2025_prj", "Liang-2023-TVR", "lipp_markus-2010-DAC", "LIPP-2007-CGA", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "LIPP-2010-PGMS", "lipp-2019-rtxq3", "LIPP-2020-PHD", "lipp-2024-val", "lipp2011a", "liu-2012-tcvd", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "Luksch_2007_RHR", "luksch_2008_asm", "luksch_2020", "LUKSCH-2009-BBC", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "Lupu-2026-Cloth", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "MAESTRI-2012-MRW", "manpreet_kainth-2012-rus", "Mantler-06-landscape", "MANTLER-2007-DMBBC", "marek-2011-normalest", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "marin-thesis", "markovich_aleksandar-2022-maa", "Martinez-2015-TTB", "maschek-2010-rts", "matt2011", "MATTAUSCH-2006-AVC", "mattausch-2007-iav", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "mattausch-2010-var", "Mattausch-2010-vcr", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "mayer_2011_cipa", "mayer_luiz-2026-baa", "MAYER-2010-MTX", "Mayer-2010-VT", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "MAYRHAUSER-2016-SCA", "mazza-2012-bakk", "Meier_2024_WIALT", "Meier_2024_WIALT", "MeierStauffer-2013-iihf", "metzger-2024-smv", "micu_2025-prj", "miklautsch_florian-baa", "MOELLINGER-2010-SD", "MORARU-2014-CPD", "mortezapoor-2022-photogrammabot", "Mortezapoor2021ssc", "Muehlbacher_2012_RRM", "Muehlbacher_2012_RTR", "MuehlbacherArbesser-2009-LMDLightcuts", "MUEHLBERGER-2010-AFSM", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2012_aachen", "musialski_2012_fice", "musialski_2016_sosp", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-prag", "musialski-2013-surcgf", "musialski-2015-ista", "musialski-2015-pixel", "musialski-2015-souos", "musialski-2015-vrvis", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "Neum03CAMR", "Neum04GCM", "neumann-2004-aip", "Neumann-2004-HOB", "neumann-2004-ipm", "neumann-2006-gamma", "neumann-sfd", "Niederreiter_2011_SM", "NIEDERREITER-2010-SIM", "NK_2011", "novak_martin-2018-baa", "Nuernberg-2011-CBO", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "ohrhallinger-stefan-2012-the", "OPPITZ-2017-3DM", "oppitz-2023-ais", "OPPTIZ-2018-IVRL", "OTEPKA-2020-PPC", "ott-rgi", "ott-va", "Pajer-2006-tmcg", "pakkanen-2026-prj", "panfili-2019-VAVR", "panfili-2021-myop", "pangerl_2013_GPD", "papantonakis-2024-rmf", "parakkat-2024-ballmerge", "parakkat-2024-ballmerge", "PARZER-2010-STELL", "PB-VRVis-2018-005", "pegrisch_2018_uvs", "Pel-2026", "PERNDORFER-2015-ECS", "pernsteiner-2022-msh", "pernsteinre_jakob_2020_eechc", "perzi_marvin-2026-baa", "Petersen_Viktoria-2024-SBO", "pezenka_lukas2012-bspcga", "pichler_2022_fro", "pichler_2022_fro", "PIRINGER-2003-HBOQ", "pirraku-f", "piskernik-2010-eud", "pistellato-2023-elp", "PLUCH-2009-ANP", "PODARAS-2017-ACRS", "Podaras-praktikum-2016", "pogrzebacz-2014-gggm", "pogrzebacz-2023-vkl", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "POLLAK-2016-STEREO", "polzer-sog", "pr10", "praeauer-2011-et", "Prast_Stefanie_2013-CLG", "preiner_2010_GIPC", "preiner_2012_AS", "preiner_2012_AS", "Preiner_2019", "PREINER-2009-GIPC", "preiner11IR", "preiner2014clop", "preissegger-2025-vrh", "Preymann-2022-pytamashii", "prieler_11_patchmatch", "prieler_daniel-2013-da", "prieler_daniel-2013-pra", "probst_kolesik_2010_pk10", "probst-2023-para", "proelss-bdp", "prohaska_julia-2023-baa", "prost-2016-molecule", "PROST-2019-RTPAL", "Przemyslaw_Gora_2016_UVU", "PUEYO-2019-SCL", "Purgathofer_2012_IVA", "purgathofer-1988-simple", "purgathofer-2004-asp", "purgathofer-2004-comp", "purgathofer-2004-neue", "purgathofer-2004-real", "purgathofer-2004-some", "Purgathofer-2005-Ros", "Purgathofer-2005-Tub", "Purgathofer-2006-VRVis", "Purgathofer-2009-rus", "purgathofer-2010-cgtrends", "Purgathofer-2014-EurasiaGr", "radax-2008-ir", "RADAX-2010-LOD", "radax-2010-RTL", "Radax2008", "radits_2011_gahdr", "Radwan_2021_Occ", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "Rainer_2017", "rait_alexius-2021-baa", "Rait2022", "rasch_martina-2013-HDRImage", "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "RAUCH-2011-TMS", "recheis-2009-arr", "REICHHOLF-2023-HRO", "Reichinger-12", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "Reimerth_Saskia_2016_RGU", "REINALTER_2010_VIS", "reinwald-2017-baa", "reisinger-2023-iad", "Reisner_2013_RSB", "Reisner_Irene_2013_R3D", "reitsamer-2008-tsud", "resch_martin-2026-baa", "reznicek-2020-fpgaray", "richter-2020-ani", "riegler_2020_framework", "roch-2007-rtt", "Roch2006", "Roegner_RHF_2010", "ROEGNER-2014-TUI", "ROEGNER-2015-IBR", "ROESSLER-2012-OGLES", "roth_2021_vdst", "roth_vdi", "roth-2023-vlk", "rozanics-lsf", "rubik_michael-2022-baa", "Rudolf_06_IDM", "rumpelnik_martin_2020_PRM", "rumpelnik_martin_2020_PRM", "Rumpelnik_Martin-2020-NPR", "rumpelnik-2022-vlk", "rumpler_2019_PPC", "Rumpler-2019-PPC", "RUMPLER-2021-VOGL", "rumpler-2023-dcmcm", "S05", "SABADELLO-2006-HEG", "sakai_2013", "SAKAI-2015-EAPI", "sakai-2021-eif", "sakai-2024-asa", "sakai-2025-stater", "sakai-thesis", "santos-2017-dacge", "sari2008mt", "SATZER-2008", "schaffarz_2018-pra", "scharl-master-thesis", "schartmueller_2018_baa", "schaukowitsch-2013-fls", "SCHAUKOWITSCH-2015-REMOTE", "SCHAUKOWITSCH-2015-STELL", "schedl-2012-dof", "schedl-2013-gP4", "schedl-thesis", "schefcik_juergen_2015_baa", "Scheiblauer-2006-DA", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "SCHEIBLAUER-2015-WFC", "scheiblauer-thesis", "scheiblauer-thesis", "scherzer_2010a", "Scherzer-2007-PCS", "SCHERZER-2008-FSR", "scherzer-2009-isvc", "SCHERZER-2012-TCM", "scherzer-eg2010", "scherzer-thesis", "scherzer2010b", "scherzer2010d", "scherzer2010e", "scherzer2011c", "scherzer2011d", "schmid_andreas_2013-prj", "schneider-sturm-2026-mia", "schober_florian_2012_aspm", "schoerkhuber_dominik-2016-baa", "scholz_2017_bac", "schrammel_sebastian_baa", "schuetz_markus-2013-pra", "SCHUETZ-2014-RRLP", "SCHUETZ-2015-HQP", "SCHUETZ-2016-POT", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-DISS", "SCHUETZ-2021-PCC", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schulz-faf", "schwaerzler_2018_phd", "schwaerzler-2009-ass", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "SCHWAERZLER-2017-SBGM", "schwarz-2024-m2m", "Schwengerer_Mathias-2022-BGL", "seczer-2025-vrs", "seidemann-bachelor-2013", "seisenbacher-cyclesafely", "Selig_2005_WRO", "Selig-2007-VegAnim", "Semmelrath-2022-IRS", "seyr-2025-lbt", "SIETZEN-2017-BBO", "silvana_2014", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "Spechtenhauser_Florian_2013_SIU", "spelitz_stefan-2012-CDTFMR", "sperl-2013-BA", "Sperl-praktikum-2016", "spielmann-2006-ner", "spitaler-2015-pbi", "spitaler-afr-2011", "SSMW09", "stappen_SteFAS", "stappen-2019-vrs", "starnberger-cli", "stauss-2025-gfd", "steiner_2016_isad", "steiner_2016_isad", "STEINER-2006-SVC", "steiner-2013-BS", "steiner-2014-da", "steinheber-2024-oto", "steinkellner-2022-dll", "steinkellner-2024-dll", "STEINLECHNER-2019-APS", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter", "Stingl_2011_RHS", "STINGL-2009-RHS", "Stoll2020", "STREICHER-2022-DSLS", "Streicher-bachelor-2013", "STU-SR-25", "sturl_andreas-caflm", "STURN-2013-LGI", "STURN-2013-LSI", "Sturn-2013-ST", "sturn-thesis", "stutter_david-2012-kft", "subtil-2006-disp", "SUNDSTEDT-2008-ASF", "sundstedt-2013-vag", "szabo_2013_ssrr", "Tanzmeister_2011_I3D", "tatzgern-2020-sst", "telaar_sina-2026-baa", "Thann_2019_01", "themmer-2018-fbx", "thurner-2019-ani", "TK_2011", "tobler02_amrmg", "tobler02_mbpls", "tobler97_hsdasr", "TOMASCHITZ-2020-EP", "TOROMANOFF-2005-ASA", "TR 193-02-2019-4", "TR-186-2-02-04", "TR-186-2-05-05", "TR-186-2-06-02", "TR-186-2-07-01", "TR-186-2-07-09", "TR-186-2-08-09", "TR-186-2-12-01", "Tragust-2012-GMHPC", "Tragust-2014-master-thesis", "traxler-1997-TRA", "trenkwalder-2008-landscape", "trenkwalder-2013-ma", "trenovatz-lpd", "trumpf_stefan_2012", "Tucek_2018", "Tucek_Tom-2016-aai", "tumpach_barbara-pra", "ulschmid-2024-reo", "ulschmid-2025-apc", "ulschmid-phdthesis", "unterguggenberger-2010-cmph", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2023-vaw", "unterguggenberger-2024-fropo", "unterguggenberger-phdthesis", "VASCO-2019-EVR", "vasiljevic-gpc", "VASILJEVS-2018-PMPL", "vis-foa", "VOELKL-2013-RTRS", "voglreiter-2023-tro", "Voglsam_2012_RTR", "Voglsam_2013_RRT", "wagentristl_stefan-2026-baa", "wagner-2024-par", "wallner_2008_ltosd", "WALLNER-2010-CSSAO", "wallner-2015-InfoTheoryPlay", "wallner-2015-ModelingRoutinization", "Wang-2016-BAC", "wang-sifuentes-2018-cgbase", "weber_2008_sh", "WEBER-2012-MIC", "WEBER-2015-PRA", "WEBER-2015-PRA1", "weidlich_2009_REL", "weidlich-2009-dispersion", "weidlich-2009-thesis", "weiner-2010-eud", "weinzierl_2012_iism", "weinzierl_heigl-2017-wh14", "Wenigwieser2007", "werdermann-va", "WESSNER-2019-PCW", "WEYDEMANN-2014-PIC", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "weydemann-praktikum-2016", "wieser-2019-ani", "wiesinger_2020_odpr", "wiesinger_2020_odpr", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wiesinger-2023-gcg", "wildt-tci", "Wilkie-2001-Ori", "Wilkie-2004-AMS", "wilkie-2006-dfs", "wilkie-2009-cc", "Wimmer-1999-FWIa", "Wimmer-1999-FWIb", "Wimmer-2001-PBI", "Wimmer-2001-Poi", "Wimmer-2003-RTE", "Wimmer-2004-LSPM", "Wimmer-2005-HOQ", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2006-PSM", "WIMMER-2006-SIV", "WIMMER-2007-GAR", "WIMMER-2007-RTR", "WIMMER-2008-ART", "WIMMER-2008-CAR", "WIMMER-2008-PVR", "WIMMER-2009-ARTR", "WIMMER-2009-ARTR2", "WIMMER-2009-ARTR3", "WIMMER-2009-CSR", "WIMMER-2009-ITC", "WIMMER-2009-VCCG", "WIMMER-2014-DWNT", "WIMMER-2015-CGFC", "WIMMER-2015-CGMC", "WIMMER-2016-FUTURIS", "WIMMER-2016-HARVEST4D", "WIMMER-2019-CGSG", "WIMMER-2020-ASG", "wimmer-2022-acd", "wimmer-2023-acd", "Win25", "WINKLER-2013-AMO", "Winkler-2017", "WINKLER-2019-PDG", "winklhofer_christoph-2013-RRMR", "winklmueller-aso", "withalm_brigitte-2022-baa", "Woerister_2012_ACS", "wolffhardt-2026-prj", "wonka-2000-VisP", "Wonka-2001-Ins", "Wonka-2001-IV", "Wonka-2003-Ins", "WONKA-2006-GVS", "x-mas-2013", "xmas-2025", "yoo-chaeran-2025-pr", "zapotocky_2013_ma", "ZAU14", "zeilinger_matthias-2020-baa", "Zezulka_Matthias-2023-MatLabOptInterface", "Zezulka-2024-FTS", "Zezulka-2025-NRL", "Zezulka-2026-FGTS", "Zezulka-2026-GridThermalSim", "zhang_le-2010-IGA", "zhang-thesis", "ZL_2011_IVIG", "zotti-2001-dip", "zotti-2003-ash", "zotti-2005-lum", "Zotti-2005-vis", "zotti-2006-dgm", "zotti-2006-pla", "zotti-2007-eg", "zotti-2007-hdr", "zotti-2007-PhD", "zotti-2007-wscg", "ZOTTI-2016-VAA", "ZOTTI-2017-BM", "ZOTTI-2017-TSP", "zsolnai-2018-gms", "zsolnai-feher-thesis-2019", "zsolnai-ist-invited-2014", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=rend", "__class": "Workgroup" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/unterguggenberger-2024-fropo/", "__class": "Publication" }, { "id": "ulschmid-2024-reo", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/195927", "title": "Real-Time Editing of Path-Traced Scenes with Prioritized Re-Rendering", "date": "2024-02", "abstract": "With recent developments in GPU ray tracing performance and (AI-accelerated) noise reduction techniques, Monte Carlo Path Tracing at real-time rates becomes a viable solution for interactive 3D scene editing, with growing support in popular software. However, even for minor edits (e.g., adjusting materials or moving small objects), current solutions usually discard previous samples and the image formation process is started from scratch. In this paper, we present two adaptive, priority-based re-rendering techniques with incremental updates, prioritizing the reconstruction of regions with high importance, before gradually moving to less important regions. The suggested methods automatically identify and schedule sampling and accumulation of immediately affected regions. An extensive user study analyzes whether such prioritized renderings are beneficial to interactive scene editing, comparing them with same-time conventional re-rendering. Our evaluation shows that even with simple prio rity policies, there is a significant preference for such incremental rendering techniques for interactive editing of small objects over full-screen re-rendering with denoising.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 378, "image_height": 323, "name": "ulschmid-2024-reo-teaser.png", "type": "image/png", "size": 254543, "path": "Publication:ulschmid-2024-reo", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/ulschmid-2024-reo/ulschmid-2024-reo-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/ulschmid-2024-reo/ulschmid-2024-reo-teaser:thumb{{size}}.png" }, "sync_repositum_override": "booktitle", "repositum_presentation_id": null, "authors": [ { "id": 1954, "drupal_id": 4406, "orcid_id": "0000-0002-0539-9378", "website": "https://www.cg.tuwien.ac.at/staff/AnnalenaUlschmid", "firstname": "Annalena", "lastname": "Ulschmid", "searchname": "Annalena Ulschmid", "is_teacher": false, "name": "Annalena Ulschmid", "publications": [ "ecormier-nocca-2025-sls", "huber-2025-esl", "ulschmid-2024-reo", "ulschmid-2025-apc", "ulschmid-phdthesis", "unterguggenberger-2023-ait" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "ABG25", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "akan-vf", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Ams25", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "antes-g", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "balvan-g", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Che-2025", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "ecormier-nocca-2025-sls", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kovacs-2025-pf", "field_id": 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"ulschmid-2025-apc", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2023-vaw", "unterguggenberger-2024-fropo", "voglreiter-2023-tro" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "gamsjaeger-2022-proc", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "HANN_2022_IPT", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "horvath_imp", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "kerbl-2022-trienc", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kimmersdorfer-2021-mzip", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "kimmersdorfer-2024-vcpr", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "kristmann-2022-occ", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "pernsteiner-2022-msh", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "pernsteinre_jakob_2020_eechc", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": 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"BOKSANSKY-2019-RTS", "brugger-2020-tdp", "CADIK-2006-IAQ", "CADIK-2008-EHD", "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "celarek_adam-2019-qelta", "celarek-2022-gmcn", "celarek-2025-d3g", "CHARALAMBOS-2007-HLOD", "CORNEL-2017-FRS", "CORNEL-2019-IVF", "dataset-viennacity", "ecormier-nocca-2025-sls", "eibens-2021-tsgpmg", "EISEMANN-2011-RTS", "EISEMANN-2012-ERT", "EISEMANN-2013-ERT", "erler_2024_ppsurf", "erler-2020-p2s", "erler-2025-lidarscout", "fink-2012-cg1", "fink-2013-cag", "freude_2020_rs", "freude-2023-prh", "freude-2023-sem", "freude-2025-iso", "freude-2025-ras", "Fritz-2012", "GIEGL-2006-QVS", "GIEGL-2007-FVS", "GIEGL-2007-QV1", "GIEGL-2007-UNP", "gilmutdinov-2022-aomlbwug", "GRELAUD-2009-EPA", "guerrero-2008-sli", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "Habel_08_SSH", "Habel_09_PGT", "Habel_2007_IAG", "Habel_2007_RTT", "Habel_2012_PSP", "Habel_LSN_2011", "Habel-2010-EIN", "hafner-2015-onff", "hecher-2014-MH", "HECHER-2017-HDY", 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"short_title": "IVILPC", "website": null, "status": "active", "short_abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

\r\n", "abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

\r\n", "start_date": "2023-07-02", "end_date": "2026-07-01", "leader_id": 166, "logo": { "name": "logo.png", "path": "project:d9275", "type": "image/png", "size": 268858, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/d9275/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [], "research_areas": [ "Geometry", "Rendering", "VR" ], "publications": [ "erler-2025-lidarscout", "goel-2024-rdr", "grammatikaki-2026-treeon", "kerbl-2024-ah3", "papantonakis-2024-rmf", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "ulschmid-2024-reo", "ulschmid-2025-apc", "unterguggenberger-2024-fropo", "voglreiter-2023-tro" ], "url": "https://www.cg.tuwien.ac.at/research/projects/IVILPC", "__class": "Project" }, { "id": "d4314", "workgroup_id": "rend", "drupal_id": 4314, "drupal_path": "/research/projects/ACD", "name": "Advanced Computational Design", "name_de": "Advanced Computational Design", "short_title": "ACD", "website": "http://acd.tuwien.ac.at", "status": "active", "short_abstract": null, "abstract": "

Research question: The main research question addressed by the SFB “Advanced Computational Design” is how to advance design tools and processes through multi- and interdisciplinary basic research in the areas of digital architecture, integrated building design, computer graphics and virtual reality, discrete and applied geometry, and computational mechanics. 

\n

Wider research context: Architecture, Engineering and Construction (AEC) shapes our built environment, exerting substantial environmental, cultural and economic influence on society. However, it is among the least digitized industries, still caught in silo-thinking and sequential planning processes. The Information and Communication Technology field, on the other hand, is highly innovative, creating digital design tools that are well-founded in basic research, but often lack relevant domain knowledge, thus hardly meeting designers’ needs.

\n

Innovation: We will connect architecture, computer science, mathematics and engineering in order to develop advanced computational design tools able to incorporate implicit and explicit design knowledge. This unique combination of scientific disciplines and collaborative research with strong theoretical foundations aims to bring radical innovation in computational design by allowing immediate feedback already in early design phases and by expanding solution spaces by computing design variants that cannot be found by current methods.

\n

Approach: The proposed research is structured in three areas: Design Methodology (A1), Visual and Haptic Design Interaction (A2) and Form Finding (A3). A1 uses ontologies to describe AEC design semantics, coupled to a novel digital mixed-reality sketchbook, and an innovative implicit modeling approach based on retrieving and enhancing 2D images and 3D point clouds through transfer learning. A1 also acts as a platform for integrating and evaluating the computational tools and methods developed in A2 and A3. These areas will investigate research questions in computational design involving algorithmic solutions. A2 investigates real-time global-illumination and optimization algorithms for lighting design, as well as a new method for large-scale haptic interactions in virtual reality based on a mobile robotic platform. In A3, form finding will be explored regarding geometric, mechanical and material constraints, in particular: paneling of complex shapes by patches of certain surface classes while optimizing the number of molds; algorithms for finding new transformable quad-surfaces; mechanical models for an efficient simulation of bio-composite material systems. Furthermore, new ways of form-finding will be explored experimentally, which will allow for validating the developed algorithmic approaches and reconsidering model assumptions and constraints.

\n

Added value: The fundamental computational tools and methods to be developed will be applicable in AEC and other fields of the creative industries.

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"4", "pages": "15", "pages_from": "1", "pages_to": "15", "publisher": "ASSOC COMPUTING MACHINERY", "volume": "42", "research_areas": [], "keywords": [ "potentially visible sets", "real-time", "occlusion" ], "weblinks": [], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 302, "image_height": 167, "name": "voglreiter-2023-tro-teaser.jpg", "type": "image/jpeg", "size": 10478, "path": "Publication:voglreiter-2023-tro", "url": "https://www.cg.tuwien.ac.at/research/publications/2023/voglreiter-2023-tro/voglreiter-2023-tro-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2023/voglreiter-2023-tro/voglreiter-2023-tro-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "d9275", "workgroup_id": "vis", "drupal_id": 9275, "drupal_path": "/research/projects/IVILPC", "name": "Instant Visualization and Interaction for Large Point Clouds", "name_de": null, "short_title": "IVILPC", "website": null, "status": "active", "short_abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

\r\n", "abstract": "

Point clouds are a quintessential 3D geometry representation format, and often the first model obtained from reconstructive efforts, such as LIDAR scans. IVILPC aims for fast, authentic, interactive, and high-quality processing of such point-based data sets. Our project explores high-performance software rendering routines for various point-based primitives, such as point sprites, gaussian splats, surfels, and particle systems. Beyond conventional use cases, point cloud rendering also forms a key component of point-based machine learning methods and novel-view synthesis, where performance is paramount. We will exploit the flexibility and processing power of cutting-edge GPU architecture features to formulate novel, high-performance rendering approaches. The envisioned solutions will be applicable to unstructured point clouds for instant rendering of billions of points. Our research targets minimally-invasive compression, culling methods, and level-of-detail techniques for point-based rendering to deliver high performance and quality on-demand. We explore GPU-accelerated editing of point clouds, as well as common display issues on next-generation display devices. IVILPC lays the foundation for interaction with large point clouds in conventional and immersive environments. Its goal is an efficient data knowledge transfer from sensor to user, with a wide range of use cases to image-based rendering, virtual reality (VR) technology, architecture, the geospatial industry, and cultural heritage.

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"LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "LIPP-2010-PGMS", "lipp-2019-rtxq3", "LIPP-2020-PHD", "lipp-2024-val", "lipp2011a", "liu-2012-tcvd", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "Luksch_2007_RHR", "luksch_2008_asm", "luksch_2020", "LUKSCH-2009-BBC", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "Lupu-2026-Cloth", "machacek_christian-2026-prj", "macho_jonas-2024-baa", "MAESTRI-2012-MRW", "manpreet_kainth-2012-rus", "Mantler-06-landscape", "MANTLER-2007-DMBBC", "marek-2011-normalest", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "marin-thesis", "markovich_aleksandar-2022-maa", "Martinez-2015-TTB", "maschek-2010-rts", "matt2011", "MATTAUSCH-2006-AVC", "mattausch-2007-iav", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "mattausch-2010-var", "Mattausch-2010-vcr", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "mayer_2011_cipa", "mayer_luiz-2026-baa", "MAYER-2010-MTX", "Mayer-2010-VT", "mayr_patrick_maa", "Mayrhauser-2016-Cnc", "MAYRHAUSER-2016-SCA", "mazza-2012-bakk", "Meier_2024_WIALT", "Meier_2024_WIALT", "MeierStauffer-2013-iihf", "metzger-2024-smv", "micu_2025-prj", "miklautsch_florian-baa", "MOELLINGER-2010-SD", "MORARU-2014-CPD", "mortezapoor-2022-photogrammabot", "Mortezapoor2021ssc", "Muehlbacher_2012_RRM", "Muehlbacher_2012_RTR", "MuehlbacherArbesser-2009-LMDLightcuts", "MUEHLBERGER-2010-AFSM", "mueller-2024-rbt", "mujadzic_iman_baa", "mujadzic-2023-hfp", "murturi_PGG", "musialski_2012_aachen", "musialski_2012_fice", "musialski_2016_sosp", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-prag", "musialski-2013-surcgf", "musialski-2015-ista", "musialski-2015-pixel", "musialski-2015-souos", "musialski-2015-vrvis", "nawrocki-2024-nsr", "negi_ashish-2023-baa", "Neum03CAMR", "Neum04GCM", "neumann-2004-aip", "Neumann-2004-HOB", "neumann-2004-ipm", "neumann-2006-gamma", "neumann-sfd", "Niederreiter_2011_SM", "NIEDERREITER-2010-SIM", "NK_2011", "novak_martin-2018-baa", "Nuernberg-2011-CBO", "ohrhallinger_stefan-2011-001", "ohrhallinger_stefan-2012-mle", "ohrhallinger_stefan-2013-c2d", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger_stefan-2022-it1", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger_stefan-2024-inv", "ohrhallinger-2016-sgp", "ohrhallinger-2016-sgp", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "ohrhallinger-stefan-2012-the", "OPPITZ-2017-3DM", "oppitz-2023-ais", "OPPTIZ-2018-IVRL", "OTEPKA-2020-PPC", "ott-rgi", "ott-va", "Pajer-2006-tmcg", "pakkanen-2026-prj", "panfili-2019-VAVR", "panfili-2021-myop", "pangerl_2013_GPD", "papantonakis-2024-rmf", "parakkat-2024-ballmerge", "parakkat-2024-ballmerge", "PARZER-2010-STELL", "PB-VRVis-2018-005", "pegrisch_2018_uvs", "Pel-2026", "PERNDORFER-2015-ECS", "pernsteiner-2022-msh", "pernsteinre_jakob_2020_eechc", "perzi_marvin-2026-baa", "Petersen_Viktoria-2024-SBO", "pezenka_lukas2012-bspcga", "pichler_2022_fro", "pichler_2022_fro", "PIRINGER-2003-HBOQ", "pirraku-f", "piskernik-2010-eud", "pistellato-2023-elp", "PLUCH-2009-ANP", "PODARAS-2017-ACRS", "Podaras-praktikum-2016", "pogrzebacz-2014-gggm", "pogrzebacz-2023-vkl", "pointner_michael-2017-baa", "pointner_simon-2022-maa", "POLLAK-2016-STEREO", "polzer-sog", "pr10", "praeauer-2011-et", "Prast_Stefanie_2013-CLG", "preiner_2010_GIPC", "preiner_2012_AS", "preiner_2012_AS", "Preiner_2019", "PREINER-2009-GIPC", "preiner11IR", "preiner2014clop", "preissegger-2025-vrh", "Preymann-2022-pytamashii", "prieler_11_patchmatch", "prieler_daniel-2013-da", "prieler_daniel-2013-pra", "probst_kolesik_2010_pk10", "probst-2023-para", "proelss-bdp", "prohaska_julia-2023-baa", "prost-2016-molecule", "PROST-2019-RTPAL", "Przemyslaw_Gora_2016_UVU", "PUEYO-2019-SCL", "Purgathofer_2012_IVA", "purgathofer-1988-simple", "purgathofer-2004-asp", "purgathofer-2004-comp", "purgathofer-2004-neue", "purgathofer-2004-real", "purgathofer-2004-some", "Purgathofer-2005-Ros", "Purgathofer-2005-Tub", "Purgathofer-2006-VRVis", "Purgathofer-2009-rus", "purgathofer-2010-cgtrends", "Purgathofer-2014-EurasiaGr", "radax-2008-ir", "RADAX-2010-LOD", "radax-2010-RTL", "Radax2008", "radits_2011_gahdr", "Radwan_2021_Occ", "Radwan-2014-CDR", "Radwan-2017-Occ", "radwan-thesis", "Rainer_2017", "rait_alexius-2021-baa", "Rait2022", "rasch_martina-2013-HDRImage", "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "RAUCH-2011-TMS", "recheis-2009-arr", "REICHHOLF-2023-HRO", "Reichinger-12", "reiher_joerg-2023-pra", "reiher-joerg-2024-daa", "Reimerth_Saskia_2016_RGU", "REINALTER_2010_VIS", "reinwald-2017-baa", "reisinger-2023-iad", "Reisner_2013_RSB", "Reisner_Irene_2013_R3D", "reitsamer-2008-tsud", "resch_martin-2026-baa", "reznicek-2020-fpgaray", "richter-2020-ani", "riegler_2020_framework", "roch-2007-rtt", "Roch2006", "Roegner_RHF_2010", "ROEGNER-2014-TUI", "ROEGNER-2015-IBR", "ROESSLER-2012-OGLES", "roth_2021_vdst", "roth_vdi", "roth-2023-vlk", "rozanics-lsf", "rubik_michael-2022-baa", "Rudolf_06_IDM", "rumpelnik_martin_2020_PRM", "rumpelnik_martin_2020_PRM", "Rumpelnik_Martin-2020-NPR", "rumpelnik-2022-vlk", "rumpler_2019_PPC", "Rumpler-2019-PPC", "RUMPLER-2021-VOGL", "rumpler-2023-dcmcm", "S05", "SABADELLO-2006-HEG", "sakai_2013", "SAKAI-2015-EAPI", "sakai-2021-eif", "sakai-2024-asa", "sakai-2025-stater", "sakai-thesis", "santos-2017-dacge", "sari2008mt", "SATZER-2008", "schaffarz_2018-pra", "scharl-master-thesis", "schartmueller_2018_baa", "schaukowitsch-2013-fls", "SCHAUKOWITSCH-2015-REMOTE", "SCHAUKOWITSCH-2015-STELL", "schedl-2012-dof", "schedl-2013-gP4", "schedl-thesis", "schefcik_juergen_2015_baa", "Scheiblauer-2006-DA", "Scheiblauer-2008-DCW", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2011-chnt", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "SCHEIBLAUER-2015-WFC", "scheiblauer-thesis", "scheiblauer-thesis", "scherzer_2010a", "Scherzer-2007-PCS", "SCHERZER-2008-FSR", "scherzer-2009-isvc", "SCHERZER-2012-TCM", "scherzer-eg2010", "scherzer-thesis", "scherzer2010b", "scherzer2010d", "scherzer2010e", "scherzer2011c", "scherzer2011d", "schmid_andreas_2013-prj", "schneider-sturm-2026-mia", "schober_florian_2012_aspm", "schoerkhuber_dominik-2016-baa", "scholz_2017_bac", "schrammel_sebastian_baa", "schuetz_markus-2013-pra", "SCHUETZ-2014-RRLP", "SCHUETZ-2015-HQP", "SCHUETZ-2016-POT", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-DISS", "SCHUETZ-2021-PCC", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schulz-faf", "schwaerzler_2018_phd", "schwaerzler-2009-ass", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "SCHWAERZLER-2017-SBGM", "schwarz-2024-m2m", "Schwengerer_Mathias-2022-BGL", "seczer-2025-vrs", "seidemann-bachelor-2013", "seisenbacher-cyclesafely", "Selig_2005_WRO", "Selig-2007-VegAnim", "Semmelrath-2022-IRS", "seyr-2025-lbt", "SIETZEN-2017-BBO", "silvana_2014", "sippl-2014-fss", "slajcho_levente-baa", "slavtchev-dcd", "Spechtenhauser_Florian_2013_SIU", "spelitz_stefan-2012-CDTFMR", "sperl-2013-BA", "Sperl-praktikum-2016", "spielmann-2006-ner", "spitaler-2015-pbi", "spitaler-afr-2011", "SSMW09", "stappen_SteFAS", "stappen-2019-vrs", "starnberger-cli", "stauss-2025-gfd", "steiner_2016_isad", "steiner_2016_isad", "STEINER-2006-SVC", "steiner-2013-BS", "steiner-2014-da", "steinheber-2024-oto", "steinkellner-2022-dll", "steinkellner-2024-dll", "STEINLECHNER-2019-APS", "steinschauer-2020-baa", "steinschorn-2023-p2m", "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter", "Stingl_2011_RHS", "STINGL-2009-RHS", "Stoll2020", "STREICHER-2022-DSLS", "Streicher-bachelor-2013", "STU-SR-25", "sturl_andreas-caflm", "STURN-2013-LGI", "STURN-2013-LSI", "Sturn-2013-ST", "sturn-thesis", "stutter_david-2012-kft", "subtil-2006-disp", "SUNDSTEDT-2008-ASF", "sundstedt-2013-vag", "szabo_2013_ssrr", "Tanzmeister_2011_I3D", "tatzgern-2020-sst", "telaar_sina-2026-baa", "Thann_2019_01", "themmer-2018-fbx", "thurner-2019-ani", "TK_2011", "tobler02_amrmg", "tobler02_mbpls", "tobler97_hsdasr", "TOMASCHITZ-2020-EP", "TOROMANOFF-2005-ASA", "TR 193-02-2019-4", "TR-186-2-02-04", "TR-186-2-05-05", "TR-186-2-06-02", "TR-186-2-07-01", "TR-186-2-07-09", "TR-186-2-08-09", "TR-186-2-12-01", "Tragust-2012-GMHPC", "Tragust-2014-master-thesis", "traxler-1997-TRA", "trenkwalder-2008-landscape", "trenkwalder-2013-ma", "trenovatz-lpd", "trumpf_stefan_2012", "Tucek_2018", "Tucek_Tom-2016-aai", "tumpach_barbara-pra", "ulschmid-2024-reo", "ulschmid-2025-apc", "ulschmid-phdthesis", "unterguggenberger-2010-cmph", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2023-vaw", "unterguggenberger-2024-fropo", "unterguggenberger-phdthesis", "VASCO-2019-EVR", "vasiljevic-gpc", "VASILJEVS-2018-PMPL", "vis-foa", "VOELKL-2013-RTRS", "voglreiter-2023-tro", "Voglsam_2012_RTR", "Voglsam_2013_RRT", "wagentristl_stefan-2026-baa", "wagner-2024-par", "wallner_2008_ltosd", "WALLNER-2010-CSSAO", "wallner-2015-InfoTheoryPlay", "wallner-2015-ModelingRoutinization", "Wang-2016-BAC", "wang-sifuentes-2018-cgbase", "weber_2008_sh", "WEBER-2012-MIC", "WEBER-2015-PRA", "WEBER-2015-PRA1", "weidlich_2009_REL", "weidlich-2009-dispersion", "weidlich-2009-thesis", "weiner-2010-eud", "weinzierl_2012_iism", "weinzierl_heigl-2017-wh14", "Wenigwieser2007", "werdermann-va", "WESSNER-2019-PCW", "WEYDEMANN-2014-PIC", "WEYDEMANN-2016-NUO", "weydemann-2025-noo", "weydemann-praktikum-2016", "wieser-2019-ani", "wiesinger_2020_odpr", "wiesinger_2020_odpr", "wiesinger_2025-baa", "wiesinger_klemens-2023-baa", "wiesinger-2023-gcg", "wildt-tci", "Wilkie-2001-Ori", "Wilkie-2004-AMS", "wilkie-2006-dfs", "wilkie-2009-cc", "Wimmer-1999-FWIa", "Wimmer-1999-FWIb", "Wimmer-2001-PBI", "Wimmer-2001-Poi", "Wimmer-2003-RTE", "Wimmer-2004-LSPM", "Wimmer-2005-HOQ", "WIMMER-2006-DWN", "WIMMER-2006-IP", "WIMMER-2006-PSM", "WIMMER-2006-SIV", "WIMMER-2007-GAR", "WIMMER-2007-RTR", "WIMMER-2008-ART", "WIMMER-2008-CAR", "WIMMER-2008-PVR", "WIMMER-2009-ARTR", "WIMMER-2009-ARTR2", "WIMMER-2009-ARTR3", "WIMMER-2009-CSR", "WIMMER-2009-ITC", "WIMMER-2009-VCCG", "WIMMER-2014-DWNT", "WIMMER-2015-CGFC", "WIMMER-2015-CGMC", "WIMMER-2016-FUTURIS", "WIMMER-2016-HARVEST4D", "WIMMER-2019-CGSG", "WIMMER-2020-ASG", "wimmer-2022-acd", "wimmer-2023-acd", "Win25", "WINKLER-2013-AMO", "Winkler-2017", "WINKLER-2019-PDG", "winklhofer_christoph-2013-RRMR", "winklmueller-aso", "withalm_brigitte-2022-baa", "Woerister_2012_ACS", "wolffhardt-2026-prj", "wonka-2000-VisP", "Wonka-2001-Ins", "Wonka-2001-IV", "Wonka-2003-Ins", "WONKA-2006-GVS", "x-mas-2013", "xmas-2025", "yoo-chaeran-2025-pr", "zapotocky_2013_ma", "ZAU14", "zeilinger_matthias-2020-baa", "Zezulka_Matthias-2023-MatLabOptInterface", "Zezulka-2024-FTS", "Zezulka-2025-NRL", "Zezulka-2026-FGTS", "Zezulka-2026-GridThermalSim", "zhang_le-2010-IGA", "zhang-thesis", "ZL_2011_IVIG", "zotti-2001-dip", "zotti-2003-ash", "zotti-2005-lum", "Zotti-2005-vis", "zotti-2006-dgm", "zotti-2006-pla", "zotti-2007-eg", "zotti-2007-hdr", "zotti-2007-PhD", "zotti-2007-wscg", "ZOTTI-2016-VAA", "ZOTTI-2017-BM", "ZOTTI-2017-TSP", "zsolnai-2018-gms", "zsolnai-feher-thesis-2019", "zsolnai-ist-invited-2014", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=rend", "__class": "Workgroup" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2023/voglreiter-2023-tro/", "__class": "Publication" } ]