[ { "id": "cardoso-thesis", "type_id": "phdthesis", "tu_id": null, "repositum_id": "20.500.12708/209309", "title": "Approaching Under-Explored Image-Space Problems with Optimization", "date": "2024-12-19", "abstract": "This doctoral dissertation delves into three distinct yet interconnected problems in the realm of interactive image-space computing in computer graphics, each of which has not been tackled by existing literature.The first problem centers on the prediction of visual error metrics in real-time applications, specifically in the context of content-adaptive shading and shading reuse. Utilizing convolutional neural networks, this research aims to estimate visual errors without requiring reference or rendered images. The models developed can account for 70%–90% of the variance and achieve computation times that are an order of magnitude faster than existing methods. This enables a balance between resource-saving and visual quality, particularly in deferred shading pipelines, and can achieve up to twice the performance compared to state-of-the-art methods depending on the portion of unseen image regions. The second problem focuses on the burgeoning field of light-field cameras and the challenges associated with depth prediction. This research argues for the refinement of cost volumes rather than depth maps to increase the accuracy of depth predictions. A set of cost-volume refinement algorithms is proposed, which dynamically operate at runtime to find optimal solutions, thereby enhancing the accuracy and reliability of depth estimation in light fields.The third problem tackles the labor-intensive nature of hand-drawn animation, specifically in the detailing of character eyes. An unsupervised network is introduced that blends inpainting and image-to-image translation techniques. This network employs a novel style-aware clustering method and a dual-discriminator optimization strategy with a triple-reconstruction loss. The result is an improvement in the level of detail and artistic consistency in hand-drawn animation, preferred over existing work 95.16% of the time according to a user study.Optimization techniques are the common thread that ties these problems together. While dynamic optimization at runtime is employed for cost volume refinement, deep-learning methods are used offline to train global solutions for the other two problems. This research not only fills gaps in the existing literature but also paves the way for future explorations in the field of computer graphics and optimization, offering new avenues for both academic research and practical applications.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": "date", "repositum_presentation_id": null, "authors": [ { "id": 1639, "drupal_id": 1489, "orcid_id": "0000-0002-6530-7244", "website": "https://www.cg.tuwien.ac.at/staff/Joao-AfonsoCardoso", "firstname": "Joao Afonso", "lastname": "Cardoso", "searchname": "Joao Afonso Cardoso", "is_teacher": false, "name": "Joao Afonso Cardoso", "publications": [ "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "cardoso-2021-cost", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "cardoso-2022-rtpercept", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "cardoso-2024-r-c", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "hanko-2019-ani", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Kugler-2021", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "metzger-2024-smv", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "richter-2020-ani", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "thurner-2019-ani", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "wieser-2019-ani", "field_id": "supervisor", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1639", "__class": "Author" } ], "ac_number": "AC17414787", "date_end": "2024-12-19", "date_start": "2019-04", "doi": "10.34726/hss.2025.128664", "matrikelnr": "11937133", "open_access": "yes", "pages": "110", "reviewer_1": [ { "id": 1825, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Amal Dev", "lastname": "Parakkat", "searchname": "Amal Dev Parakkat", "is_teacher": false, "name": "Amal Dev Parakkat", "publications": [ "marin-2024-sing", "ohrhallinger_stefan-2022-tut", "ohrhallinger_stefan-2023-con", "ohrhallinger-2021-egs", "ohrhallinger-2022-e2t", "parakkat-2024-ballmerge" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "cardoso-thesis", "field_id": "reviewer_1", "ordernum": 0 }, { "publ_id": "ohrhallinger-2021-egs", "field_id": "lecturer", "ordernum": 2 }, { "publ_id": "ohrhallinger-2022-e2t", "field_id": "lecturer", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1825", "__class": "Author" } ], "reviewer_2": [ { "id": 5420, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Jorge", "lastname": "Manuel de Oliveira Henrique", "searchname": "Jorge Manuel de Oliveira Henrique", "is_teacher": false, "name": "Jorge Manuel de Oliveira Henrique", "publications": [], "publications_first": [], "project_leader": [], 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"In this area, our research focuses on understanding and using the capabilities of human perception for designing high-quality graphics algorithms and effective visualizations.", "abstract": "

In computer graphics we produce images, videos, visualizations and other content that is perceived by humans. By understanding the limits of human perception, we can design and optimize rendering algorithms that perfectly fit users' needs, tailor visualizations to make data better understandable, and effectively draw the user's attention to important information.

\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/Perception", "teaser": { "name": "teaser.PNG", "path": "research_area:Perception", "type": "image/png", "size": 259428, "orig_name": "teaser.PNG", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Perception/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend", "vis" ], "publications": [ "bernhard-2011-maicg", "bernhard-2014-EFD", "bernhard-2014-GTOM", "bernhard-2016-gft", "birkeland_aasmund_2014_pums", "cardoso-2022-rtpercept", "cardoso-thesis", "ERLER-2017-HVR", "eschner-2023-ims", "eschner-blur-2022", "georgiev-2019-cbg", "Groeller_2016_P7", "grossmann-2021-layout", "hecher-2012-MH", "hecher-2014-MH", "HECHER-2017-HDY", "huerbe-2019-BA", "Kathi-2018-VRB", "koch-2019-PR", "Koszticsak-2017-ewt", "kraehsmaier-dsc", "KREUZER-2017-PBF", "kristmann-2022-occ", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-ThesisFF", "kroesl-2020-XREye", "Laschober-2018", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "mayr-2021-wec", "mindek-2017-dsn", "pahr-2024-ieo", "panfili-2019-VAVR", "panfili-2021-myop", "plank-2017-sldg", "polatsek-2018-stv", "Reichinger-2016-spaghetti", "schindler_2020vis", "schuller_reichl-2019-avt", "Semmelrath-2022-IRS", "stappen_SteFAS", "steinkellner-2022-dll", "sundstedt-2013-vag", "thesis-kronsteiner", "trautner-2018-imd", "Vasylevska_Khrystyna-2019-TEFVR", "viola-evr", "Waldin_Nicholas_2016_Colormaps", "Waldin_Nicholas_2016_Individualization", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldner-2013-facetCloudsGI", "waldner-2014-af", "waldner-2017-vph", "waldner-2019-rld" ], "projects": [ "CROSSMOD" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Perception", "__class": "ResearchArea" }, { "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", "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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The Collegium will train the next generation of creative, entrepreneurial and innovative experts who will be equipped with the necessary skills and competences to face current and future major challenges in scalable and high-fidelity geometry and material acquisition, extraction of structure and semantic information, processing, visualization, 3D display and 3D fabrication in professional and consumer applications. In the future, the ESRs will lead research and development of new visual and geometric computing methods in the widest variety of applications, ranging from industrial design to humanities, from medical training to urban assessment, and from creative industries to education methodologies. The EVOCATION network of public and private entities will be naturally multidisciplinary and multi-institutional and will: (a) promote, through domain-specific challenges, the culture of open science and multidisciplinary research applied to concrete problems of the real world, in strict cooperation with end users in engineering, science and humanities; (b) advance the state-of- the-art in geometry and material acquisition, geometry processing and semantic feature extraction, interactive visualization, computational fabrication, and high-bandwidth/3D display systems; (c) bridge complementary approaches for cost-effective data digitization, visualization, fabrication, and display through the integration of different methodologies in the 3D capture, processing and fabrication pipeline; (d) demonstrate the feasibility and efficiency of scalable cost-effective end-to-end techniques to virtually and physically capture and create objects with complex shape and appearance; (e) increase awareness of the benefits of advanced visual/geometric computing technology in both professional and consumer domains.", "start_date": "2018-10-01", "end_date": "2023-06-30", "leader_id": 193, "logo": { "name": "logo.png", "path": "project:EVOCATION", "type": "image/png", "size": 34154, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/EVOCATION/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "Horizon 2020", "contract_number": "ITN 813170", "comment": null } ], "research_areas": [ "Fabrication", "Geometry", "Modeling", "Rendering" ], "publications": [ "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "celarek_adam-2019-qelta", "celarek-2022-gmcn", "FRAISS-2022-CGMM", "hanko-2019-ani", "richter-2020-ani", "thurner-2019-ani", "wieser-2019-ani" ], "url": "https://www.cg.tuwien.ac.at/research/projects/EVOCATION", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/cardoso-thesis/", "__class": "Publication" }, { "id": "cardoso-2024-r-c", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/209907", "title": "Re:Draw - Context Aware Translation as a Controllable Method for Artistic Production", "date": "2024-08", "abstract": "We introduce context-aware translation, a novel method that combines the benefits of inpainting and image-to-image translation, respecting simultaneously the original input and contextual relevance – where existing methods fall short. By doing so, our method opens new avenues for the controllable use of AI within artistic creation, from animation to digital art.\nAs an use case, we apply our method to redraw any hand-drawn animated character eyes based on any design specifications – eyes serve as a focal point that captures viewer attention and conveys a range of emotions; however, the labor-intensive na-\nture of traditional animation often leads to compromises in the complexity and consistency of eye design. Furthermore, we remove the need for production data for training and introduce a new character recognition method that surpasses existing work\nby not requiring fine-tuning to specific productions.\nThis proposed use case could help maintain consistency throughout production and unlock bolder and\nmore detailed design choices without the production cost drawbacks. A user study shows contextaware translation is preferred over existing work 95.16% of the time.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 343, "image_height": 294, "name": "cardoso-2024-r-c-image.bmp", "type": "image/bmp", "size": 303462, "path": "Publication:cardoso-2024-r-c", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/cardoso-2024-r-c/cardoso-2024-r-c-image.bmp", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/cardoso-2024-r-c/cardoso-2024-r-c-image:thumb{{size}}.png" }, "sync_repositum_override": "date,projects", "repositum_presentation_id": null, "authors": [ { "id": 1639, "drupal_id": 1489, "orcid_id": "0000-0002-6530-7244", "website": "https://www.cg.tuwien.ac.at/staff/Joao-AfonsoCardoso", "firstname": "Joao Afonso", "lastname": "Cardoso", "searchname": "Joao Afonso Cardoso", "is_teacher": false, "name": "Joao Afonso Cardoso", "publications": [ "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "cardoso-2021-cost", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "cardoso-2022-rtpercept", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "cardoso-2024-r-c", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "hanko-2019-ani", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Kugler-2021", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "metzger-2024-smv", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "richter-2020-ani", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "thurner-2019-ani", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "wieser-2019-ani", "field_id": "supervisor", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1639", "__class": "Author" }, { "id": 5437, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Francesco", "lastname": "Banterle", "searchname": "Francesco Banterle", "is_teacher": false, "name": "Francesco Banterle", "publications": [ "cardoso-2024-r-c" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5437", "__class": "Author" }, { "id": 1519, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Paolo", "lastname": "Cignoni", "searchname": "Paolo Cignoni", "is_teacher": false, "name": "Paolo Cignoni", "publications": [ "cardoso-2024-r-c", "WIMMER-2016-HARVEST4D" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "erler_philipp-2017-phd", "field_id": "reviewer_2", "ordernum": 0 } ], "url": 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"rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2023-ani", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "RASOULZADEH-2026-PREDICTING", "reisinger-2023-iad", "ROEGNER-2015-IBR", "roth_vdi", "sakai-2021-eif", "sakai-2024-asa", "sakai-2025-stater", "santos-2017-dacge", "schedl-2012-dof", "schedl-2013-gP4", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "SCHEIBLAUER-2015-WFC", "scherzer_2010a", "Scherzer-2007-PCS", "SCHERZER-2008-FSR", "scherzer-2009-isvc", "SCHERZER-2012-TCM", "scherzer-eg2010", "scherzer2011c", "scherzer2011d", "SCHUETZ-2015-HQP", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2019-PCC", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "SCHUETZ-2026-CURAST", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "SCHWAERZLER-2017-SBGM", "SSMW09", "stappen_SteFAS", 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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", "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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"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": [ "Application domains: Images, movies and visual arts", "Application domains: Computer Graphics and Animation", "Methods and resources: AI systems for collaboration and co-creation", "Methods and resources: Machine learning, deep learning, neural models, reinforcement learning", "Theory and philosophy of arts and creativity in AI systems: Social (multi-agent) creativity and human-computer co-creation" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 343, "image_height": 294, "name": "cardoso-2024-r-c-image.bmp", "type": "image/bmp", "size": 303462, "path": "Publication:cardoso-2024-r-c", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/cardoso-2024-r-c/cardoso-2024-r-c-image.bmp", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/cardoso-2024-r-c/cardoso-2024-r-c-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "cardoso-2024-r-c-paper.pdf", "type": "application/pdf", "size": 2952059, "path": "Publication:cardoso-2024-r-c", "url": "https://www.cg.tuwien.ac.at/research/publications/2024/cardoso-2024-r-c/cardoso-2024-r-c-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2024/cardoso-2024-r-c/cardoso-2024-r-c-paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "EVOCATION", "workgroup_id": "rend", "drupal_id": 4162, "drupal_path": "/research/projects/EVOCATION", "name": "Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication", "name_de": null, "short_title": "EVOCATION", "website": null, "status": "active", "short_abstract": "This Marie-Curie project creates a leading European-wide doctoral college for research in Advanced Visual and Geometric\r\nComputing for 3D Capture, Display, and Fabrication.", "abstract": "The project will create a leading European-wide doctoral Collegium for research in Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication (EVOCATION). The Collegium will train the next generation of creative, entrepreneurial and innovative experts who will be equipped with the necessary skills and competences to face current and future major challenges in scalable and high-fidelity geometry and material acquisition, extraction of structure and semantic information, processing, visualization, 3D display and 3D fabrication in professional and consumer applications. In the future, the ESRs will lead research and development of new visual and geometric computing methods in the widest variety of applications, ranging from industrial design to humanities, from medical training to urban assessment, and from creative industries to education methodologies. The EVOCATION network of public and private entities will be naturally multidisciplinary and multi-institutional and will: (a) promote, through domain-specific challenges, the culture of open science and multidisciplinary research applied to concrete problems of the real world, in strict cooperation with end users in engineering, science and humanities; (b) advance the state-of- the-art in geometry and material acquisition, geometry processing and semantic feature extraction, interactive visualization, computational fabrication, and high-bandwidth/3D display systems; (c) bridge complementary approaches for cost-effective data digitization, visualization, fabrication, and display through the integration of different methodologies in the 3D capture, processing and fabrication pipeline; (d) demonstrate the feasibility and efficiency of scalable cost-effective end-to-end techniques to virtually and physically capture and create objects with complex shape and appearance; (e) increase awareness of the benefits of advanced visual/geometric computing technology in both professional and consumer domains.", "start_date": "2018-10-01", "end_date": "2023-06-30", "leader_id": 193, "logo": { "name": "logo.png", "path": "project:EVOCATION", "type": "image/png", "size": 34154, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/EVOCATION/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "Horizon 2020", "contract_number": "ITN 813170", "comment": null } ], "research_areas": [ "Fabrication", "Geometry", "Modeling", "Rendering" ], "publications": [ "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "celarek_adam-2019-qelta", "celarek-2022-gmcn", "FRAISS-2022-CGMM", "hanko-2019-ani", "richter-2020-ani", "thurner-2019-ani", "wieser-2019-ani" ], "url": "https://www.cg.tuwien.ac.at/research/projects/EVOCATION", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/cardoso-2024-r-c/", "__class": "Publication" }, { "id": "cardoso-2022-rtpercept", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/142206", "title": "Training and Predicting Visual Error for Real-Time Applications", "date": "2022-05", "abstract": "Visual error metrics play a fundamental role in the quantification of perceived image similarity. Most recently, use cases for them in real-time applications have emerged, such as content-adaptive shading and shading reuse to increase performance and improve efficiency. A wide range of different metrics has been established, with the most sophisticated being capable of capturing the perceptual characteristics of the human visual system. However, their complexity, computational expense, and reliance on reference images to compare against prevent their generalized use in real-time, restricting such applications to using only the simplest available metrics.\n\nIn this work, we explore the abilities of convolutional neural networks to predict a variety of visual metrics without requiring either reference or rendered images. Specifically, we train and deploy a neural network to estimate the visual error resulting from reusing shading or using reduced shading rates. The resulting models account for 70%--90% of the variance while achieving up to an order of magnitude faster computation times. Our solution combines image-space information that is readily available in most state-of-the-art deferred shading pipelines with reprojection from previous frames to enable an adequate estimate of visual errors, even in previously unseen regions. We describe a suitable convolutional network architecture and considerations for data preparation for training. We demonstrate the capability of our network to predict complex error metrics at interactive rates in a real-time application that implements content-adaptive shading in a deferred pipeline. Depending on the portion of unseen image regions, our approach can achieve up to 2x performance compared to state-of-the-art methods.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1920, "image_height": 1088, "name": "cardoso-2022-rtpercept-teaser.png", "type": "image/png", "size": 2493649, "path": "Publication:cardoso-2022-rtpercept", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/cardoso-2022-rtpercept/cardoso-2022-rtpercept-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/cardoso-2022-rtpercept/cardoso-2022-rtpercept-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1639, "drupal_id": 1489, "orcid_id": "0000-0002-6530-7244", "website": "https://www.cg.tuwien.ac.at/staff/Joao-AfonsoCardoso", "firstname": "Joao Afonso", "lastname": "Cardoso", "searchname": "Joao Afonso Cardoso", "is_teacher": false, "name": "Joao Afonso Cardoso", "publications": [ "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "cardoso-2021-cost", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "cardoso-2022-rtpercept", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "cardoso-2024-r-c", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "hanko-2019-ani", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Kugler-2021", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "metzger-2024-smv", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "richter-2020-ani", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "thurner-2019-ani", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": 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visualizations.", "abstract": "

In computer graphics we produce images, videos, visualizations and other content that is perceived by humans. By understanding the limits of human perception, we can design and optimize rendering algorithms that perfectly fit users' needs, tailor visualizations to make data better understandable, and effectively draw the user's attention to important information.

\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/Perception", "teaser": { "name": "teaser.PNG", "path": "research_area:Perception", "type": "image/png", "size": 259428, "orig_name": "teaser.PNG", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Perception/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend", "vis" ], "publications": [ "bernhard-2011-maicg", "bernhard-2014-EFD", "bernhard-2014-GTOM", "bernhard-2016-gft", "birkeland_aasmund_2014_pums", "cardoso-2022-rtpercept", "cardoso-thesis", "ERLER-2017-HVR", "eschner-2023-ims", "eschner-blur-2022", "georgiev-2019-cbg", "Groeller_2016_P7", "grossmann-2021-layout", "hecher-2012-MH", "hecher-2014-MH", "HECHER-2017-HDY", "huerbe-2019-BA", "Kathi-2018-VRB", "koch-2019-PR", "Koszticsak-2017-ewt", "kraehsmaier-dsc", "KREUZER-2017-PBF", "kristmann-2022-occ", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-ThesisFF", "kroesl-2020-XREye", "Laschober-2018", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "mayr-2021-wec", "mindek-2017-dsn", "pahr-2024-ieo", "panfili-2019-VAVR", "panfili-2021-myop", "plank-2017-sldg", "polatsek-2018-stv", "Reichinger-2016-spaghetti", "schindler_2020vis", "schuller_reichl-2019-avt", "Semmelrath-2022-IRS", "stappen_SteFAS", "steinkellner-2022-dll", "sundstedt-2013-vag", "thesis-kronsteiner", "trautner-2018-imd", "Vasylevska_Khrystyna-2019-TEFVR", "viola-evr", "Waldin_Nicholas_2016_Colormaps", "Waldin_Nicholas_2016_Individualization", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldner-2013-facetCloudsGI", "waldner-2014-af", "waldner-2017-vph", "waldner-2019-rld" ], "projects": [ "CROSSMOD" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Perception", "__class": "ResearchArea" }, { "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", "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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"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-2026-vtc", "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", "LIPP-2026-HAIR", "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", "RAOULZADEH-2026-STROKES2DEFORM", "rasch_martina-2013-HDRImage", "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "RASOULZADEH-2026-PREDICTING", "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", "SCHUETZ-2026-CURAST", "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-2026-naadf", "ulschmid-2026-naadf", "ulschmid-phdthesis", "unterguggenberger-2010-cmph", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2023-vaw", "unterguggenberger-2024-fropo", "UNTERGUGGENBERGER-2026-ALOD", "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" }, { "id": "EVOCATION", "workgroup_id": "rend", "drupal_id": 4162, "drupal_path": "/research/projects/EVOCATION", "name": "Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication", "name_de": null, "short_title": "EVOCATION", "website": null, "status": "active", "short_abstract": "This Marie-Curie project creates a leading European-wide doctoral college for research in Advanced Visual and Geometric\r\nComputing for 3D Capture, Display, and Fabrication.", "abstract": "The project will create a leading European-wide doctoral Collegium for research in Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication (EVOCATION). The Collegium will train the next generation of creative, entrepreneurial and innovative experts who will be equipped with the necessary skills and competences to face current and future major challenges in scalable and high-fidelity geometry and material acquisition, extraction of structure and semantic information, processing, visualization, 3D display and 3D fabrication in professional and consumer applications. In the future, the ESRs will lead research and development of new visual and geometric computing methods in the widest variety of applications, ranging from industrial design to humanities, from medical training to urban assessment, and from creative industries to education methodologies. The EVOCATION network of public and private entities will be naturally multidisciplinary and multi-institutional and will: (a) promote, through domain-specific challenges, the culture of open science and multidisciplinary research applied to concrete problems of the real world, in strict cooperation with end users in engineering, science and humanities; (b) advance the state-of- the-art in geometry and material acquisition, geometry processing and semantic feature extraction, interactive visualization, computational fabrication, and high-bandwidth/3D display systems; (c) bridge complementary approaches for cost-effective data digitization, visualization, fabrication, and display through the integration of different methodologies in the 3D capture, processing and fabrication pipeline; (d) demonstrate the feasibility and efficiency of scalable cost-effective end-to-end techniques to virtually and physically capture and create objects with complex shape and appearance; (e) increase awareness of the benefits of advanced visual/geometric computing technology in both professional and consumer domains.", "start_date": "2018-10-01", "end_date": "2023-06-30", "leader_id": 193, "logo": { "name": "logo.png", "path": "project:EVOCATION", "type": "image/png", "size": 34154, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/EVOCATION/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "Horizon 2020", "contract_number": "ITN 813170", "comment": null } ], "research_areas": [ "Fabrication", "Geometry", "Modeling", "Rendering" ], "publications": [ "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "celarek_adam-2019-qelta", "celarek-2022-gmcn", "FRAISS-2022-CGMM", "hanko-2019-ani", "richter-2020-ani", "thurner-2019-ani", "wieser-2019-ani" ], "url": "https://www.cg.tuwien.ac.at/research/projects/EVOCATION", "__class": "Project" }, { "id": "3DSpatialization", "workgroup_id": "rend", "drupal_id": 4156, "drupal_path": "/research/projects/3DSpatialization", "name": "Smart Communities and Technologies: 3D Spatialization", "name_de": null, "short_title": "3DSpatialization", "website": "https://smartct.tuwien.ac.at/", "status": "active", "short_abstract": "

The Research Cluster \"Smart Communities and Technologies\" (Smart CT) at TU Wien will provide the scientific underpinnings for next-generation complex smart city and communities infrastructures. Cities are ever-evolving, complex cyber physical systems of systems covering a magnitude of different areas. The initial concept of smart cities and communities started with cities utilizing communication technologies to deliver services to their citizens and evolved to using information technology to be smarter and more efficient about the utilization of their resources. In recent years however, information technology has changed significantly, and with it the resources and areas addressable by a smart city have broadened considerably. They now cover areas like smart buildings, smart products and production, smart traffic systems and roads, autonomous driving, smart grids for managing energy hubs and electric car utilization or urban environmental systems research.

\r\n\r\n

3D spatialization creates the link between the internet of cities infrastructure and the actual 3D world in which a city is embedded in order to perform advanced computation and visualization tasks. Sensors, actuators and users are embedded in a complex 3D environment that is constantly changing. Acquiring, modeling and visualizing this dynamic 3D environment are the challenges we need to face using methods from Visual Computing and Computer Graphics. 3D Spatialization aims to make a city aware of its 3D environment, allowing it to perform spatial reasoning to solve problems like visibility, accessibility, lighting, and energy efficiency.

\r\n", "abstract": "

The Research Cluster \"Smart Communities and Technologies\" (Smart CT) at TU Wien will provide the scientific underpinnings for next-generation complex smart city and communities infrastructures. Cities are ever-evolving, complex cyber physical systems of systems covering a magnitude of different areas. The initial concept of smart cities and communities started with cities utilizing communication technologies to deliver services to their citizens and evolved to using information technology to be smarter and more efficient about the utilization of their resources. In recent years however, information technology has changed significantly, and with it the resources and areas addressable by a smart city have broadened considerably. They now cover areas like smart buildings, smart products and production, smart traffic systems and roads, autonomous driving, smart grids for managing energy hubs and electric car utilization or urban environmental systems research.

\r\n\r\n

3D spatialization creates the link between the internet of cities infrastructure and the actual 3D world in which a city is embedded in order to perform advanced computation and visualization tasks. Sensors, actuators and users are embedded in a complex 3D environment that is constantly changing. Acquiring, modeling and visualizing this dynamic 3D environment are the challenges we need to face using methods from Visual Computing and Computer Graphics. 3D Spatialization aims to make a city aware of its 3D environment, allowing it to perform spatial reasoning to solve problems like visibility, accessibility, lighting, and energy efficiency.

\r\n", "start_date": "2018-02-01", "end_date": "2022-07-31", "leader_id": 193, "logo": { "name": "logo.png", "path": "project:3DSpatialization", "type": "image/png", "size": 134233, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/3DSpatialization/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [], "research_areas": [ "Geometry", "Modeling", "Rendering" ], "publications": [ "Arleo-2019-vis", "celarek-2022-gmcn", "gamsjaeger-2022-proc", "HANN_2022_IPT", "horvath_imp", "kenzel_michael_2021_cuda", "kerbl_2019_planet_poster", "kerbl_2021_hdg", "kerbl-2020-improvencoding", "kerbl-2022-cuda", "kerbl-2022-trienc", "kristmann-2022-occ", "murturi_PGG", "pernsteinre_jakob_2020_eechc", "roth_2021_vdst", "roth_vdi", "rumpelnik_martin_2020_PRM", "Rumpelnik_Martin-2020-NPR", "SCHUETZ-2021-PCC", "stappen_SteFAS", "tatzgern-2020-sst", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan" ], "url": "https://www.cg.tuwien.ac.at/research/projects/3DSpatialization", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2022/celarek-2022-gmcn/", "__class": "Publication" }, { "id": "FRAISS-2022-CGMM", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/19748", "title": "Construction and Visualization of Gaussian Mixture Models from Point Clouds for 3D Object Representation", "date": "2022-03-10", "abstract": "Point clouds are a common representation of three-dimensional shapes in computer graphics\nand 3D-data processing. However, in some applications, other representations are more useful.\nGaussian Mixture Models (GMMs) can be used as such an alternative representation. A GMM\nis a convex sum of normal distributions, which aims to describe a point cloud’s density. In\nthis thesis, we investigate both visualization and construction of GMMs. For visualization,\nwe have implemented a tool that enables both isoellipsoid and density visualization of GMMs.\nWe describe the mathematical backgrounds, the algorithms, and our implementation of this\ntool. Regarding GMM construction, we investigate several algorithms used in previous papers\nfor constructing GMMs for 3D-data processing tasks. We present our implementations of the\nexpectation-maximization (EM) algorithm and top-down HEM. Additionally, we have adapted\nthe implementation of geometrically regularized bottom-up HEM to produce a fixed number of\nGaussians. We evaluate these three algorithms in terms of the quality of their generated GMMs.\nIn many cases, the statistical likelihood, which is maximized by the EM algorithm, is not a\nreliable indicator for a GMM’s quality. Therefore, we instead rely on the reconstruction error of a\nreconstructed point cloud based on the Chamfer distance. Additionally, we provide metrics for\nmeasuring the reconstructed point cloud’s uniformity and the GMM’s variation of Gaussians. We\ndemonstrate that EM provides the best results in terms of these metrics. Top-down HEM is a fast\nalternative, and can produce even better results when using fewer input points. The results of\ngeometrically regularized bottom-up HEM are inferior for lower numbers of Gaussians but it can\ncreate good GMMs consisting of high numbers of Gaussians very eciently.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1380, "image_height": 1850, "name": "FRAISS-2022-CGMM-image.jpg", "type": "image/jpeg", "size": 376815, "path": "Publication:FRAISS-2022-CGMM", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/FRAISS-2022-CGMM/FRAISS-2022-CGMM-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/FRAISS-2022-CGMM/FRAISS-2022-CGMM-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1495, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Simon Maximilian ", "lastname": "Fraiss", "searchname": "Simon Maximilian Fraiss", "is_teacher": false, "name": "Simon Maximilian Fraiss", "publications": [ "FRAISS-2017-PCU", "fraiss-2019-rtx", "FRAISS-2022-CGMM" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1495", "__class": "Author" } ], "co_supervisor": [ { "id": 1013, "drupal_id": 613, "orcid_id": "0009-0006-8571-4150", "website": "https://www.cg.tuwien.ac.at/staff/AdamCelarek", "firstname": "Adam", "lastname": "Celarek", "searchname": "Adam Celarek", "is_teacher": false, "name": "Adam Celarek", "publications": [ "celarek_adam-2012-rrmro", "celarek_adam-2019-qelta", "CELAREK-2017-QCL", "celarek-2022-gmcn", "celarek-2025-d3g", "celarek-thesis", "eschner-2023-evl", "komon-2025-dco", "komon-2025-webigeo", "ohrhallinger_stefan-2019-xms" ], "publications_first": [], "project_leader": [ "d10214" ], "publication_field": [ { "publ_id": "celarek_adam-2019-qelta", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "celarek-2022-gmcn", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "dworschak-2024-aml", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "eschner-2023-rar", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "FRAISS-2022-CGMM", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "kimmersdorfer-fancyMaps-2023", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "komon-kimmersdorfer-2025-weBIGeo", "field_id": "supervisor", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1013", "__class": "Author" } ], "date_end": "2022-03-10", "date_start": "2021-01-01", "diploma_examina": "2022-03-10", "matrikelnr": "01425602", "supervisor": [ { "id": 193, "drupal_id": 49, "orcid_id": "0000-0002-9370-2663", "website": "https://www.cg.tuwien.ac.at/staff/MichaelWimmer", "firstname": "Michael", "lastname": "Wimmer", "searchname": "Michael Wimmer", "is_teacher": true, "name": "Michael Wimmer", "publications": [ "arikan-2013-osn", "arikan-2014-pcvis", "arikan-2015-dmrt", "Arleo-2019-vis", "Artusi-2003-Del", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", "Auzinger_Mistelbauer_2013_CSR", "bagar2010", "bernhard-2010-gph", "bernhard-2011-bmtf", "bernhard-2011-maicg", "bernhard-2014-EFD", "bernhard-2014-GTOM", "birsak-2013-sta", "birsak-2014-agtb", "birsak-2017-dpe", "Bittner-2001-Vis", "Bittner-2004-CHC", "bittner-2005-egsr", "BITTNER-2009-AGVS", "BITTNER-2009-GEFOC", "bittner-2011-scc", "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", "Honic_2021", "honic-2020-w78", "HU-2017-ETM", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2011-pmous", "ilcik-2013-cipmi", "ilcik-2016-cescg", "ilcik-2016-cmssg", "JAHRMANN-2013-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-ISTAR", "Jeschke-2002-LEM", "Jeschke-2002-LEMA", "Jeschke-2002-TDM", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "Jimenez_SSS_2015", "Kathi-2018-VRB", "kerbl-2020-improvencoding", "kerbl-2022-trienc", "kerbl-2024-ah3", "klaffenboeck-2024-rva", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "knecht-2011-CBCM", "KOCH-2021-GVS", "koenigsberger-2024-msu", "kovacs-2023-ttm", "KREUZER-2015-DPA", "kristmann-2026-vtc", "Kroesl_2020_11_09", "kroesl-2017-LiteMaker", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2020-XREye", "leimer_2017_rbpesc", "leimer-2016-rpe", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "LIPP-2010-PGMS", "lipp-2024-val", "LIPP-2026-HAIR", "lipp2011a", "luidolt-2020-lightperceptionVR", "luksch_2020", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "MANTLER-2007-DMBBC", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "matt2011", "MATTAUSCH-2006-AVC", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-surcgf", "musialski-2015-souos", "ohrhallinger_stefan-2013-smi", "ohrhallinger_stefan-2018-cgf", "ohrhallinger_stefan-2018-pg", "ohrhallinger-2016-sgp", "OTEPKA-2020-PPC", "panfili-2021-myop", "pistellato-2023-elp", "preiner_2010_GIPC", "preiner_2012_AS", "Preiner_2019", "preiner2014clop", "PUEYO-2019-SCL", "PURGATHOFER-2006-IHB", "Radwan_2021_Occ", "Radwan-2014-CDR", "Radwan-2017-Occ", "RAOULZADEH-2026-STROKES2DEFORM", "rasoulzadeh-2022-strokes2surface", "rasoulzadeh-2023-ani", "rasoulzadeh-2024-strokes2surface", "rasoulzadeh-2025-archcomplete", "RASOULZADEH-2026-PREDICTING", "reisinger-2023-iad", "ROEGNER-2015-IBR", "roth_vdi", "sakai-2021-eif", "sakai-2024-asa", "sakai-2025-stater", "santos-2017-dacge", "schedl-2012-dof", "schedl-2013-gP4", "SCHEIBLAUER-2009-IDCE", "scheiblauer-2011-cag", "scheiblauer-2012-chnt", "scheiblauer-2013-wscg", "SCHEIBLAUER-2015-WFC", "scherzer_2010a", "Scherzer-2007-PCS", "SCHERZER-2008-FSR", "scherzer-2009-isvc", "SCHERZER-2012-TCM", "scherzer-eg2010", "scherzer2011c", "scherzer2011d", "SCHUETZ-2015-HQP", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2019-PCC", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "SCHUETZ-2026-CURAST", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "SCHWAERZLER-2017-SBGM", "SSMW09", "stappen_SteFAS", "steiner_2016_isad", "STEINLECHNER-2019-APS", "STURN-2013-LGI", "STURN-2013-LSI", "SUNDSTEDT-2008-ASF", "sundstedt-2013-vag", "TR 193-02-2019-4", "TR 193-2-2019-4", "TR-186-2-02-04", "TR-186-2-07-01", "TR-186-2-07-09", "TR-186-2-12-01", "ulschmid-2024-reo", "ulschmid-2025-apc", "ulschmid-2026-naadf", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2023-vaw", "unterguggenberger-2024-fropo", "UNTERGUGGENBERGER-2026-ALOD", "wallner-2015-ModelingRoutinization", "WEBER-2015-PRA", "Wimmer-1996-ITB", "Wimmer-1997-ITT", "Wimmer-1998-Fas", "Wimmer-1998-SMO", "Wimmer-1999-FWIa", "Wimmer-1999-FWIb", "Wimmer-2001-CCL", "Wimmer-2001-PBI", "Wimmer-2001-Poi", "Wimmer-2003-RTE", "Wimmer-2004-LSPM", "Wimmer-2005-HOQ", "Wimmer-2006", "WIMMER-2006-CES", "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", "Wimmer-thesis", "wonka-2000-VisP", "wonka-2000-VisX", "Wonka-2001-Ins", "Wonka-2001-IV", "Wonka-2003-Ins", "WONKA-2006-GVS", "xmas-2023", "ymca", "ZOTTI-2016-VAA", "ZOTTI-2017-BM", "ZOTTI-2017-TSP", "zsolnai-2018-gms", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "publications_first": [], "project_leader": [ "3DSpatialization", "CROSSMOD", "d10070", "d10169", "d4307", "d4314", "d4342", "d4386", "d4559", "d4729", "d4958", "d4984", "d9259", "Desiree", "EVOCATION", "GameTools", "GAMEWORLD", "GPV", "Harvest4D", "INTRA-SPACE", "Landspotting", "Mofa", "OpenData", "PAMINA", "PathSpace", "Photo-Guide", "REPLICATE", "Scanopy", "SCI_BIM", "ShapeAcquisition", "TERAPOINTS", "Treelumination", "UrbanViz", "Wohnen 4.0" ], "publication_field": [ { "publ_id": "ADORJAN-2013-ASE", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Adorjan-2015", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "agyemang-2021-bsdfproxyppg", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "aichner-2016-sadf", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "akan-vf", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Ams25", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "antes_sebastian-2026-msc", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "antes-g", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "arikan-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "ASCHL-2022-OTV", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "AUER-2010-PPT3D", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "ausserer-2026-baa", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "auzinger-2015-phd", "field_id": "reviewer_2", "ordernum": 0 }, { "publ_id": "auzinger-2015-phd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "auzinger-dissertation", "field_id": "reviewer_2", "ordernum": 0 }, { "publ_id": "auzinger-dissertation", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "BAGAR-2010-LPB", "field_id": "supervisor", "ordernum": 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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", "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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"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": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1380, "image_height": 1850, "name": "FRAISS-2022-CGMM-image.jpg", "type": "image/jpeg", "size": 376815, "path": "Publication:FRAISS-2022-CGMM", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/FRAISS-2022-CGMM/FRAISS-2022-CGMM-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/FRAISS-2022-CGMM/FRAISS-2022-CGMM-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "FRAISS-2022-CGMM-Master thesis.pdf", "type": "application/pdf", "size": 20842982, "path": "Publication:FRAISS-2022-CGMM", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/FRAISS-2022-CGMM/FRAISS-2022-CGMM-Master thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/FRAISS-2022-CGMM/FRAISS-2022-CGMM-Master thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "FRAISS-2022-CGMM-poster.pdf", "type": "application/pdf", "size": 4483975, "path": "Publication:FRAISS-2022-CGMM", "url": "https://www.cg.tuwien.ac.at/research/publications/2022/FRAISS-2022-CGMM/FRAISS-2022-CGMM-poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2022/FRAISS-2022-CGMM/FRAISS-2022-CGMM-poster:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "EVOCATION", "workgroup_id": "rend", "drupal_id": 4162, "drupal_path": "/research/projects/EVOCATION", "name": "Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication", "name_de": null, "short_title": "EVOCATION", "website": null, "status": "active", "short_abstract": "This Marie-Curie project creates a leading European-wide doctoral college for research in Advanced Visual and Geometric\r\nComputing for 3D Capture, Display, and Fabrication.", "abstract": "The project will create a leading European-wide doctoral Collegium for research in Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication (EVOCATION). The Collegium will train the next generation of creative, entrepreneurial and innovative experts who will be equipped with the necessary skills and competences to face current and future major challenges in scalable and high-fidelity geometry and material acquisition, extraction of structure and semantic information, processing, visualization, 3D display and 3D fabrication in professional and consumer applications. In the future, the ESRs will lead research and development of new visual and geometric computing methods in the widest variety of applications, ranging from industrial design to humanities, from medical training to urban assessment, and from creative industries to education methodologies. The EVOCATION network of public and private entities will be naturally multidisciplinary and multi-institutional and will: (a) promote, through domain-specific challenges, the culture of open science and multidisciplinary research applied to concrete problems of the real world, in strict cooperation with end users in engineering, science and humanities; (b) advance the state-of- the-art in geometry and material acquisition, geometry processing and semantic feature extraction, interactive visualization, computational fabrication, and high-bandwidth/3D display systems; (c) bridge complementary approaches for cost-effective data digitization, visualization, fabrication, and display through the integration of different methodologies in the 3D capture, processing and fabrication pipeline; (d) demonstrate the feasibility and efficiency of scalable cost-effective end-to-end techniques to virtually and physically capture and create objects with complex shape and appearance; (e) increase awareness of the benefits of advanced visual/geometric computing technology in both professional and consumer domains.", "start_date": "2018-10-01", "end_date": "2023-06-30", "leader_id": 193, "logo": { "name": "logo.png", "path": "project:EVOCATION", "type": "image/png", "size": 34154, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/EVOCATION/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "Horizon 2020", "contract_number": "ITN 813170", "comment": null } ], "research_areas": [ "Fabrication", "Geometry", "Modeling", "Rendering" ], "publications": [ "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "celarek_adam-2019-qelta", "celarek-2022-gmcn", "FRAISS-2022-CGMM", "hanko-2019-ani", "richter-2020-ani", "thurner-2019-ani", "wieser-2019-ani" ], "url": "https://www.cg.tuwien.ac.at/research/projects/EVOCATION", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2022/FRAISS-2022-CGMM/", "__class": "Publication" }, { "id": "cardoso-2021-cost", "type_id": "inproceedings", "tu_id": 301688, "repositum_id": null, "title": "Cost Volume Refinement for Depth Prediction", "date": "2021-01-10", "abstract": "Light-field cameras are becoming more popular in\nthe consumer market. Their data redundancy allows, in theory,\nto accurately refocus images after acquisition and to predict the\ndepth of each point visible from the camera. Combined, these\ntwo features allow for the generation of full-focus images, which\nis impossible in traditional cameras.\nMultiple methods for depth prediction from light fields (or\nstereo) have been proposed over the years. A large subset of\nthese methods relies on cost-volume estimates – 3D objects where\neach layer represents a heuristic of whether each point in the\nimage is at a certain distance from the camera. Generally, this\nvolume is used to regress a depth map, which is then refined\nfor better results. In this paper, we argue that refining the cost\nvolumes is superior to refining the depth maps in order to further\nincrease the accuracy of depth predictions. We propose a set of\ncost-volume refinement algorithms and show their effectiveness.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "header", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 217, "image_height": 145, "name": "cardoso-2021-cost-header.jpg", "type": "image/jpeg", "size": 34129, "path": "Publication:cardoso-2021-cost", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/cardoso-2021-cost/cardoso-2021-cost-header.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/cardoso-2021-cost/cardoso-2021-cost-header:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1639, "drupal_id": 1489, "orcid_id": "0000-0002-6530-7244", "website": "https://www.cg.tuwien.ac.at/staff/Joao-AfonsoCardoso", "firstname": "Joao Afonso", "lastname": "Cardoso", "searchname": "Joao Afonso Cardoso", "is_teacher": false, "name": "Joao Afonso Cardoso", "publications": [ "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "cardoso-2021-cost", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "cardoso-2022-rtpercept", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "cardoso-2024-r-c", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "hanko-2019-ani", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Kugler-2021", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "metzger-2024-smv", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "richter-2020-ani", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "thurner-2019-ani", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "wieser-2019-ani", "field_id": "supervisor", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1639", "__class": "Author" }, { "id": 1801, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Nuno", "lastname": "Goncalves", "searchname": "Nuno Goncalves", "is_teacher": false, "name": "Nuno Goncalves", "publications": [ "cardoso-2021-cost" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1801", "__class": "Author" }, { "id": 193, "drupal_id": 49, "orcid_id": "0000-0002-9370-2663", "website": "https://www.cg.tuwien.ac.at/staff/MichaelWimmer", "firstname": "Michael", "lastname": "Wimmer", "searchname": "Michael Wimmer", "is_teacher": true, "name": "Michael Wimmer", "publications": [ "arikan-2013-osn", "arikan-2014-pcvis", "arikan-2015-dmrt", "Arleo-2019-vis", "Artusi-2003-Del", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", 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"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", "Honic_2021", "honic-2020-w78", "HU-2017-ETM", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2011-pmous", "ilcik-2013-cipmi", "ilcik-2016-cescg", "ilcik-2016-cmssg", "JAHRMANN-2013-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-ISTAR", "Jeschke-2002-LEM", "Jeschke-2002-LEMA", "Jeschke-2002-TDM", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "Jimenez_SSS_2015", "Kathi-2018-VRB", "kerbl-2020-improvencoding", "kerbl-2022-trienc", "kerbl-2024-ah3", "klaffenboeck-2024-rva", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "knecht-2011-CBCM", "KOCH-2021-GVS", "koenigsberger-2024-msu", "kovacs-2023-ttm", "KREUZER-2015-DPA", "kristmann-2026-vtc", "Kroesl_2020_11_09", "kroesl-2017-LiteMaker", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2020-XREye", "leimer_2017_rbpesc", "leimer-2016-rpe", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "LIPP-2010-PGMS", "lipp-2024-val", "LIPP-2026-HAIR", "lipp2011a", "luidolt-2020-lightperceptionVR", "luksch_2020", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "MANTLER-2007-DMBBC", "marin-2022-sig", "marin-2022-sigdt", "marin-2023-pic", "marin-2024-dsr", "marin-2024-pcp", "marin-2024-rcf", "marin-2024-sing", "marin-2026-sor", "matt2011", "MATTAUSCH-2006-AVC", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "murturi_PGG", "musialski_2016_sosp", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-surcgf", "musialski-2015-souos", 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[ { "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", "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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"KOCH-2021-GVS", "KOCH-2021-GVSDA", "KOEPPEL-2025-Nearfield", "Koeppl-2023-DLO", "Komon2022", "Konev-FCV2018", "Kovacs_2017", "kovacs-2025-pf", "KREUZER-2015-DPA", "KREUZER-2017-PBF", "kristmann-2022-occ", "kristmann-2023-vkl", "kristmann-2026-vtc", "KRISTMANN-24-JPG", "kroesl-2017-LiteMaker", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-ThesisFF", "KROESL-2020-SVI", "kroesl-2020-XREye", "KUE11", "Kugler-2021", "Lan25", "leopold-2019-vox", "Liang-2023-TVR", "lipp-2019-rtxq3", "LIPP-2020-PHD", "lipp-2024-val", "LIPP-2026-HAIR", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "luksch_2020", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "Mantler-06-landscape", "MANTLER-2007-DMBBC", "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", 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"WEBER-2015-PRA1", "weidlich_2009_REL", "weidlich-2009-dispersion", "weidlich-2009-thesis", "weinzierl_heigl-2017-wh14", "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": [ "depth reconstruction", "light fields", "cost volumes" ], "weblinks": [], "files": [ { "description": "Acknowledgements section added.", "filetitle": "amended-paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "cardoso-2021-cost-amended-paper.pdf", "type": "application/pdf", "size": 11789393, "path": "Publication:cardoso-2021-cost", "url": 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"name": "cardoso-2021-cost-original-paper.pdf", "type": "application/pdf", "size": 11772629, "path": "Publication:cardoso-2021-cost", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/cardoso-2021-cost/cardoso-2021-cost-original-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/cardoso-2021-cost/cardoso-2021-cost-original-paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "EVOCATION", "workgroup_id": "rend", "drupal_id": 4162, "drupal_path": "/research/projects/EVOCATION", "name": "Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication", "name_de": null, "short_title": "EVOCATION", "website": null, "status": "active", "short_abstract": "This Marie-Curie project creates a leading European-wide doctoral college for research in Advanced Visual and Geometric\r\nComputing for 3D Capture, Display, and Fabrication.", "abstract": "The project will create a leading European-wide doctoral Collegium for research in Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication (EVOCATION). The Collegium will train the next generation of creative, entrepreneurial and innovative experts who will be equipped with the necessary skills and competences to face current and future major challenges in scalable and high-fidelity geometry and material acquisition, extraction of structure and semantic information, processing, visualization, 3D display and 3D fabrication in professional and consumer applications. In the future, the ESRs will lead research and development of new visual and geometric computing methods in the widest variety of applications, ranging from industrial design to humanities, from medical training to urban assessment, and from creative industries to education methodologies. The EVOCATION network of public and private entities will be naturally multidisciplinary and multi-institutional and will: (a) promote, through domain-specific challenges, the culture of open science and multidisciplinary research applied to concrete problems of the real world, in strict cooperation with end users in engineering, science and humanities; (b) advance the state-of- the-art in geometry and material acquisition, geometry processing and semantic feature extraction, interactive visualization, computational fabrication, and high-bandwidth/3D display systems; (c) bridge complementary approaches for cost-effective data digitization, visualization, fabrication, and display through the integration of different methodologies in the 3D capture, processing and fabrication pipeline; (d) demonstrate the feasibility and efficiency of scalable cost-effective end-to-end techniques to virtually and physically capture and create objects with complex shape and appearance; (e) increase awareness of the benefits of advanced visual/geometric computing technology in both professional and consumer domains.", "start_date": "2018-10-01", "end_date": "2023-06-30", "leader_id": 193, "logo": { "name": "logo.png", "path": "project:EVOCATION", "type": "image/png", "size": 34154, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/EVOCATION/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "Horizon 2020", "contract_number": "ITN 813170", "comment": null } ], "research_areas": [ "Fabrication", "Geometry", "Modeling", "Rendering" ], "publications": [ "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "celarek_adam-2019-qelta", "celarek-2022-gmcn", "FRAISS-2022-CGMM", "hanko-2019-ani", "richter-2020-ani", "thurner-2019-ani", "wieser-2019-ani" ], "url": "https://www.cg.tuwien.ac.at/research/projects/EVOCATION", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/cardoso-2021-cost/", "__class": "Publication" }, { "id": "hanko-2019-ani", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Higher Hand-Drawn Detail Quality using Convolutional Assistant", "date": "2020-04", "abstract": "The field of research in the use of neural networks to help artists or advance 2D animation\nis very underdeveloped. Most of the little research that is done does not even ask questions\nthat are relevant for animators but is done in a pure research mindset. We, however,\ntried to find a problem that would actually be relevant in the animation industry and\ncame up with the idea of enhancing the feature quality of poorly drawn features in 2D\nanimation. The basis for this idea is that, as a cost and time-saving measure, in 2d\nanimation features are often drawn in different levels of detail depending on the current\nfocus of the scene and other factors. The focus will thereby lie on the enhancement of\ncharacters’ eyes with the idea that other features could be done in a similar way in future\nwork. To achieve this quality enhancing we train the FUNIT network on a\nmanually created dataset consisting of crops of eyes from different characters in different\nquality with the goal that it will be able to consistently transform low-quality eye images\ninto high-quality eye images", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 217, "image_height": 145, "name": "hanko-2019-ani-teaser.jpg", "type": "image/jpeg", "size": 45990, "path": "Publication:hanko-2019-ani", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/hanko-2019-ani/hanko-2019-ani-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/hanko-2019-ani/hanko-2019-ani-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1744, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Dominik", "lastname": "Hanko", "searchname": "Dominik Hanko", "is_teacher": false, "name": "Dominik Hanko", "publications": [ "hanko-2019-ani" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1744", "__class": "Author" } ], "date_end": "2020-04", "date_start": "2019-10", "matrikelnr": "01625726", "supervisor": [ { "id": 1639, "drupal_id": 1489, "orcid_id": "0000-0002-6530-7244", "website": "https://www.cg.tuwien.ac.at/staff/Joao-AfonsoCardoso", "firstname": "Joao Afonso", "lastname": "Cardoso", "searchname": "Joao Afonso Cardoso", "is_teacher": false, "name": "Joao Afonso Cardoso", "publications": [ "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "cardoso-2021-cost", "field_id": "lecturer", "ordernum": 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"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" } ], "research_areas": [], "keywords": [], "weblinks": [], "files": { "1": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 217, "image_height": 145, "name": "hanko-2019-ani-teaser.jpg", "type": "image/jpeg", "size": 45990, "path": "Publication:hanko-2019-ani", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/hanko-2019-ani/hanko-2019-ani-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/hanko-2019-ani/hanko-2019-ani-teaser:thumb{{size}}.png" } }, "projects_workgroups": [ { "id": "EVOCATION", "workgroup_id": "rend", "drupal_id": 4162, "drupal_path": "/research/projects/EVOCATION", "name": "Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication", "name_de": null, "short_title": "EVOCATION", "website": null, "status": "active", "short_abstract": "This Marie-Curie project creates a leading European-wide doctoral college for research in Advanced Visual and Geometric\r\nComputing for 3D Capture, Display, and Fabrication.", "abstract": "The project will create a leading European-wide doctoral Collegium for research in Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication (EVOCATION). The Collegium will train the next generation of creative, entrepreneurial and innovative experts who will be equipped with the necessary skills and competences to face current and future major challenges in scalable and high-fidelity geometry and material acquisition, extraction of structure and semantic information, processing, visualization, 3D display and 3D fabrication in professional and consumer applications. In the future, the ESRs will lead research and development of new visual and geometric computing methods in the widest variety of applications, ranging from industrial design to humanities, from medical training to urban assessment, and from creative industries to education methodologies. The EVOCATION network of public and private entities will be naturally multidisciplinary and multi-institutional and will: (a) promote, through domain-specific challenges, the culture of open science and multidisciplinary research applied to concrete problems of the real world, in strict cooperation with end users in engineering, science and humanities; (b) advance the state-of- the-art in geometry and material acquisition, geometry processing and semantic feature extraction, interactive visualization, computational fabrication, and high-bandwidth/3D display systems; (c) bridge complementary approaches for cost-effective data digitization, visualization, fabrication, and display through the integration of different methodologies in the 3D capture, processing and fabrication pipeline; (d) demonstrate the feasibility and efficiency of scalable cost-effective end-to-end techniques to virtually and physically capture and create objects with complex shape and appearance; (e) increase awareness of the benefits of advanced visual/geometric computing technology in both professional and consumer domains.", "start_date": "2018-10-01", "end_date": "2023-06-30", "leader_id": 193, "logo": { "name": "logo.png", "path": "project:EVOCATION", "type": "image/png", "size": 34154, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/EVOCATION/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "Horizon 2020", "contract_number": "ITN 813170", "comment": null } ], "research_areas": [ "Fabrication", "Geometry", "Modeling", "Rendering" ], "publications": [ "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "celarek_adam-2019-qelta", "celarek-2022-gmcn", "FRAISS-2022-CGMM", "hanko-2019-ani", "richter-2020-ani", "thurner-2019-ani", "wieser-2019-ani" ], "url": "https://www.cg.tuwien.ac.at/research/projects/EVOCATION", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/hanko-2019-ani/", "__class": "Publication" }, { "id": "wieser-2019-ani", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Classification of Production Ready 2D Animation using Contour and Distance Fields", "date": "2019-12", "abstract": "Image classification is one of the most common use cases of Convolutional Neural Networks. In this thesis, our goal is to increase the accuracy of a neural network classifier for frames of production ready 2D animations and to create a model from a dataset with high accuracy for classification. This can be seen as groundwork for future work that applies neural networks on production ready 2D animation data, by reusing and tweaking the model for different applications.\n\nWe compare training a neural network with the color channels of images to training with\ngrayscale images, predicted contours or distance fields generated from those contours.\nFurthermore, different combinations of the data will be used to evaluate the best option.\nThis means that the comparison of the accuracy not only includes color data compared\nto color with contours and distance fields but every combination of the aforementioned\nfour types of input.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 217, "image_height": 145, "name": "wieser-2019-ani-teaser.jpg", "type": "image/jpeg", "size": 14419, "path": "Publication:wieser-2019-ani", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wieser-2019-ani/wieser-2019-ani-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wieser-2019-ani/wieser-2019-ani-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1657, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Manuel", "lastname": "Wieser", "searchname": "Manuel Wieser", "is_teacher": false, "name": "Manuel Wieser", "publications": [ "wieser-2019-ani" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1657", "__class": "Author" } ], "date_end": "2019-12", "date_start": "2019-06", "matrikelnr": "01633066", "supervisor": [ { "id": 193, "drupal_id": 49, "orcid_id": "0000-0002-9370-2663", "website": "https://www.cg.tuwien.ac.at/staff/MichaelWimmer", 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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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The Collegium will train the next generation of creative, entrepreneurial and innovative experts who will be equipped with the necessary skills and competences to face current and future major challenges in scalable and high-fidelity geometry and material acquisition, extraction of structure and semantic information, processing, visualization, 3D display and 3D fabrication in professional and consumer applications. In the future, the ESRs will lead research and development of new visual and geometric computing methods in the widest variety of applications, ranging from industrial design to humanities, from medical training to urban assessment, and from creative industries to education methodologies. The EVOCATION network of public and private entities will be naturally multidisciplinary and multi-institutional and will: (a) promote, through domain-specific challenges, the culture of open science and multidisciplinary research applied to concrete problems of the real world, in strict cooperation with end users in engineering, science and humanities; (b) advance the state-of- the-art in geometry and material acquisition, geometry processing and semantic feature extraction, interactive visualization, computational fabrication, and high-bandwidth/3D display systems; (c) bridge complementary approaches for cost-effective data digitization, visualization, fabrication, and display through the integration of different methodologies in the 3D capture, processing and fabrication pipeline; (d) demonstrate the feasibility and efficiency of scalable cost-effective end-to-end techniques to virtually and physically capture and create objects with complex shape and appearance; (e) increase awareness of the benefits of advanced visual/geometric computing technology in both professional and consumer domains.", "start_date": "2018-10-01", "end_date": "2023-06-30", "leader_id": 193, "logo": { "name": "logo.png", "path": "project:EVOCATION", "type": "image/png", "size": 34154, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/EVOCATION/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "Horizon 2020", "contract_number": "ITN 813170", "comment": null } ], "research_areas": [ "Fabrication", "Geometry", "Modeling", "Rendering" ], "publications": [ "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "celarek_adam-2019-qelta", "celarek-2022-gmcn", "FRAISS-2022-CGMM", "hanko-2019-ani", "richter-2020-ani", "thurner-2019-ani", "wieser-2019-ani" ], "url": "https://www.cg.tuwien.ac.at/research/projects/EVOCATION", "__class": "Project" }, { "id": "OpenData", "workgroup_id": "rend", "drupal_id": 4183, "drupal_path": "/research/projects/OpenData", "name": "A Test Suite for Photorealistic Rendering and Filtering", "name_de": null, "short_title": "OpenData", "website": null, "status": "active", "short_abstract": "This project will research methods to test and compare global-illumination algorithms as well as filtering algorithms, and also develop test data sets for this purpose.", "abstract": "Rendering photorealistic images has been a long-standing problem in computer graphics. 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