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        "id": "erler-2020-p2s",
        "type_id": "inproceedings",
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        "repositum_id": "20.500.12708/55555",
        "title": "Points2Surf: Learning Implicit Surfaces from Point Clouds",
        "date": "2020-10-28",
        "abstract": "A key step in any scanning-based asset creation workflow is to convert unordered point clouds to a surface. Classical methods (e.g., Poisson reconstruction) start to degrade in the presence of noisy and partial scans. Hence, deep learning based methods have recently been proposed to produce complete surfaces, even from partial scans. However, such data-driven methods struggle to generalize to new shapes with large geometric and topological variations. We present Points2Surf, a novel patch-based learning framework that produces accurate surfaces directly from raw scans without normals.\n\nLearning a prior over a combination of detailed local patches and coarse global information improves generalization performance and reconstruction accuracy.\n\nOur extensive comparison on both synthetic and real data demonstrates a clear advantage of our method over state-of-the-art alternatives on previously unseen classes (on average, Points2Surf brings down reconstruction error by 30% over SPR and by 270%+ over deep learning based SotA methods) at the cost of longer computation times and a slight increase in small-scale topological noise in some cases. \nOur source code, pre-trained model, and dataset are available on: https://github.com/ErlerPhilipp/points2surf\n",
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            "description": "We present Points2Surf, a method to reconstruct an accurate implicit surface from a noisy point cloud. Unlike current data-driven surface reconstruction methods like DeepSDF and AtlasNet, it is patch-based, improves detail reconstruction, and unlike Screened Poisson Reconstruction (SPR), a learned prior of low-level patch shapes improves reconstruction accuracy. \nNote the quality of reconstructions, both geometric and topological, against the original surfaces. The ability of Points2Surf to generalize to new shapes makes it the first learning-based approach with significant generalization ability under both geometric and topological variations.",
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        "pages": "17",
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        "publisher": "Springer International Publishing",
        "series": "Lecture Notes in Computer Science",
        "volume": "12350",
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                "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ",
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                    "rozanics-lsf",
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                    "schuh-2018-mesh-blending",
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                    "seisenbacher-cyclesafely",
                    "sippl-2014-fss",
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                    "slavtchev-dcd",
                    "starnberger-cli",
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                    "Traxler-1996-CTB",
                    "trenovatz-lpd",
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                    "unterguggenberger-2021-msh",
                    "Vucenovic_2022",
                    "wagentristl_stefan-2026-baa",
                    "WEYDEMANN-2016-NUO",
                    "weydemann-2025-noo",
                    "wiesinger_2025-baa",
                    "wiesinger_klemens-2023-baa",
                    "Wimmer-1998-SMO",
                    "WIMMER-2006-DWN",
                    "WIMMER-2006-IP",
                    "WIMMER-2016-HARVEST4D",
                    "withalm_brigitte-2022-baa",
                    "wolffhardt-2026-prj",
                    "yoo-chaeran-2025-pr",
                    "zeilinger_matthias-2020-baa",
                    "Zezulka-2024-FTS"
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                    "d4388",
                    "d9275",
                    "EVOCATION",
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                    "SCI_BIM",
                    "ShapeAcquisition",
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                    "TERAPOINTS",
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                    "Adorjan-2015",
                    "aichner-2016-sadf",
                    "arikan-2013-osn",
                    "birsak-thesis",
                    "Birsak2018-SA",
                    "Brandstaetter2020",
                    "brunner_lukas_2022_ssb",
                    "Caic2021",
                    "clemenz_2019_rosy_fields",
                    "DOG10",
                    "dusberger-2010-msm",
                    "eibens-2021-tsgpmg",
                    "eibensteiner-2021-pmcg",
                    "eibner-2009-gpc",
                    "Erhardt_2025_Scutes",
                    "erler_2024_ppsurf",
                    "erler_philipp-2016-femfluid-prakt",
                    "erler_philipp-2017-phd",
                    "erler-2020-p2s",
                    "erler-2025-lidarscout",
                    "fan-2014-scfl",
                    "ferschin-1992-kons",
                    "fiedler-2009-php",
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                    "gamsjaeger-2022-proc",
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                    "gervautz-1989-sol1",
                    "gervautz-1993-use",
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                    "groeller-1992-frac",
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                    "Groeller-1995-SDC",
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                "abstract": "<p>In recent years, virtual and augmented reality have gained widespread attention because of newly developed head-mounted displays. For the first time, mass-market penetration seems plausible. Also, range sensors are on the verge of being integrated into smartphones, evidenced by prototypes such as the Google Tango device, making ubiquitous on-line acquisition of 3D data a possibility. The combination of these two technologies – displays and sensors – promises applications where users can directly be immersed into an experience of 3D data that was just captured live. However, the captured data needs to be processed and structured before being displayed. For example, sensor noise needs to be removed, normals need to be estimated for local surface reconstruction, etc. The challenge is that these operations involve a large amount of data, and in order to ensure a lag-free user experience, they need to be performed in real time, i.e., in just a few milliseconds per frame. In this proposal, we exploit the fact that dynamic point clouds captured in real time are often only relevant for display and interaction in the current frame and inside the current view frustum. In particular, we propose a new view-dependent data structure that permits efficient connectivity creation and traversal of unstructured data, which will speed up surface recovery, e.g. for collision detection. Classifying occlusions comes at no extra cost, which will allow quick access to occluded layers in the current view. This enables new methods to explore and manipulate dynamic 3D scenes, overcoming interaction methods that rely on physics-based metaphors like walking or flying, lifting interaction with 3D environments to a “superhuman” level.</p>\r\n",
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                    "VR"
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                "website": null,
                "status": "active",
                "short_abstract": "The aim of this project is to investigate and to contribute to shape modeling and geometry processing for personal fabrication---a trend that currently receives intensified attention in the science and industry. Our goal is to contribute novel algorithmic solutions for fabrication-aware shape processing and interactive modeling. ",
                "abstract": "The aim of this project is to investigate and to contribute to shape modeling and geometry processing for personal fabrication---a trend that currently receives intensified attention in the science and industry. \nOur goal is to contribute novel algorithmic solutions for fabrication-aware shape processing and interactive modeling. In particular, we want to research following aspects: (i) We want to address the currently pending problem of high-level shape understanding, (ii) we want to research novel high-level shape modeling methods for interactive creation of plausible and aesthetically appealing shapes, and finally, (iii) we want to address optimization problems related to instant desktop 3D printing, such that modeled objects can be directly fabricated. The outcome of the project will be a set of algorithmic solutions for high-level shape modeling for instant personal fabrication.",
                "start_date": "2015-04-01",
                "end_date": "2020-03-31",
                "leader_id": 844,
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                    "Birsak2018-SA",
                    "erler-2020-p2s",
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                    "leimer_2017_rbpesc",
                    "leimer_2020-cag",
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                    "leimer-2016-rpe",
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                    "musialski-2015-ista",
                    "musialski-2015-pixel",
                    "musialski-2015-souos",
                    "musialski-2015-vrvis",
                    "steiner_2016_isad",
                    "WINKLER-2019-PDG"
                ],
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                "id": "ShapeAcquisition",
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                "short_title": "ShapeAcquisition",
                "website": null,
                "status": "active",
                "short_abstract": "Acquiring shapes of physical objects in real time and with guaranteed precision to the noise model of the sensor devices.",
                "abstract": "<p>The core idea in this project is to capture the shape of physical objects in real time, with guaranteed precision, and to reconstruct the shape boundaries with minimal geometry. An example application is to let untrained users acquire shapes using emerging mobile sensing devices such as Google’s Project Tango. The user moves the sensor around the object, guided by immediate visual feedback on the input sampling quality. The output is a topologically clean mesh consisting of just the vertices required to represent its features to the desired approximation. The real-time reconstruction enables numerous geometry-processing applications to be taken online, such as shape retrieval/matching, harvesting real-world geometry into a cloud, perspective photo correction, interactive modeling, augmented reality, physics simulation, or fabrication.</p>\r\n",
                "start_date": "2015-12-01",
                "end_date": "2020-11-30",
                "leader_id": 193,
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                    "grossmann-2016-baa",
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                    "koeppel-2016-baa",
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        "id": "leimer_2020-cag",
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        "repositum_id": "20.500.12708/141145",
        "title": "Pose to Seat: Automated design of body-supporting surfaces",
        "date": "2020-04",
        "abstract": "The design of functional seating furniture is a complicated process which often requires extensive manual design effort and empirical evaluation. We propose a computational design framework for pose-driven automated generation of body-supports which are optimized for comfort of sitting. Given a human body in a specified pose as input, our method computes an approximate pressure distribution that also takes frictional forces and body torques into consideration which serves as an objective measure of comfort. Utilizing this information to find out where the body needs to be supported in order to maintain comfort of sitting, our algorithm can create a supporting mesh suited for a person in that specific pose. This is done in an automated fitting process, using a template model capable of supporting a large variety of sitting poses. The results can be used directly or can be considered as a starting point for further interactive design.",
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                    "marin-2024-rcf",
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        ],
        "date_from": "2020-01-01",
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        "event": "Conference",
        "journal": "Computer Aided Geometric Design",
        "open_access": "yes",
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        "pages_to": "1",
        "volume": "79",
        "research_areas": [
            {
                "id": "Fabrication",
                "drupal_id": 4132,
                "name": "Fabrication",
                "short_abstract": "The advent of consumer-grade 3D printing has recently sparked interest in fabrication-aware shape design and optimization. We use techniques from computer graphics and engineering to develop new computational tools to facilitate the design process of physical artifacts.",
                "abstract": "The task of finding the perfect shape of a real-world object that fulfills a given objective optimally appears in many disciplines, like interior design, building planning, or construction of machine parts. These tasks can be subject to considerations of functionality, cost-effciency, and aesthetics, as well as constraints relating to size, producibility, safety margins, etc. The great complexity and the presence of conflicting and hard-to-formalize goals have hitherto precluded automation of many design tasks and leave them in the hands of human designers and engineers.\n\nThere is, however, great potential to aid these processes computationally and to unlock difficult design tasks for a larger audience. This will not only provide faster work flows and enable the exploration of new design spaces, but it constitutes a necessary step towards the wide-spread application of personalized fabrication techniques like additive manufacturing. Low-cost 3d printing has been widely described as a disruptive technology and the herald of a new industrial revolution. These expectations have since been tempered by a reality which shows that availability alone is inconsequential unless accompanied by an innovation of supporting technologies.\n\nThe big challenge in making new fabrication techniques more useful is the development of a computational design methodology that relieves its users of low-level tasks like explicit 3d modeling and provides tools to create shapes from functional, aesthetic, and other high-level specifications. The overarching goal of this research area is to find new mathematical models and computational solutions fordesign tasks that are at this time tedious or impossible at all.",
                "website": "https://www.cg.tuwien.ac.at/research/area/Fabrication",
                "teaser": {
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                    "path": "research_area:Fabrication",
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                    "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Fabrication/teaser:thumb{{size}}.png",
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                    "gersthofer-2016-sosob",
                    "hafner-2015-eigf",
                    "hafner-2015-onff",
                    "korpitsch_thorsten-2019",
                    "korpitsch-2020-cescg",
                    "leimer_2020-cag",
                    "leimer-2018-sar",
                    "musialski_2016_sosp",
                    "musialski-2015-souos",
                    "pahr-2021-vologram",
                    "pahr-2024-squishicalization",
                    "Reichinger-2016-spaghetti",
                    "schindler_2020vis",
                    "schultes_lampi",
                    "Staudacher_2022",
                    "walchhofer-tso",
                    "WINKLER-2019-PDG"
                ],
                "projects": [
                    "EVOCATION",
                    "MAKE-IT-FAB"
                ],
                "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Fabrication",
                "__class": "ResearchArea"
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            {
                "id": "Geometry",
                "drupal_id": 4129,
                "name": "Geometry Processing",
                "short_abstract": "Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.",
                "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ",
                "website": "https://www.cg.tuwien.ac.at/research/area/Geometry",
                "teaser": {
                    "name": "teaser.png",
                    "path": "research_area:Geometry",
                    "type": "image/png",
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                    "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Geometry/teaser:thumb{{size}}.png",
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                    "arikan-2013-osn",
                    "ausserer-2026-baa",
                    "balvan-rsf",
                    "bayer_bernhard-2026-baa",
                    "beleznai_csaba-2025-pr",
                    "belic_dejan_pr",
                    "bodzenta-2026-baa",
                    "brunner_lukas_2022_ssb",
                    "celarek-2022-gmcn",
                    "clemenz_2019_rosy_fields",
                    "cornel-2022-wih",
                    "csecsy-fcd",
                    "darovskikh_leonid-2025-prj",
                    "deak-a3",
                    "depner_dennis-2020-baa",
                    "depner_dennis-2022-maa",
                    "Doerflinger-2016-CDV",
                    "elagrod_ahmed-baa",
                    "Erhardt_2025_Scutes",
                    "erler_2024_ppsurf",
                    "erler_philipp-2017-phd",
                    "erler-2020-p2s",
                    "erler-2025-lidarscout",
                    "fitzinger_andreas-daa",
                    "forsythe-2016-ccm",
                    "fraissl_niklas-2023-pra",
                    "fuchs_peter-2024-baa",
                    "fuericht_2025_prj",
                    "fuericht_elias-2025-prj",
                    "gamsjaeger-2022-proc",
                    "gersthofer-2016-sosob",
                    "geyer_lukas_2015_prj",
                    "Grossfurtner-2023-paego",
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                "id": "Superhumans",
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                "name": "Superhumans - Walking Through Walls",
                "name_de": null,
                "short_title": "Superhumans",
                "website": null,
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                "short_abstract": "<p>In recent years, virtual and augmented reality have gained widespread attention because of newly developed head-mounted displays. For the first time, mass-market penetration seems plausible. Also, range sensors are on the verge of being integrated into smartphones, evidenced by prototypes such as the Google Tango device, making ubiquitous on-line acquisition of 3D data a possibility. The combination of these two technologies – displays and sensors – promises applications where users can directly be immersed into an experience of 3D data that was just captured live. However, the captured data needs to be processed and structured before being displayed. For example, sensor noise needs to be removed, normals need to be estimated for local surface reconstruction, etc. The challenge is that these operations involve a large amount of data, and in order to ensure a lag-free user experience, they need to be performed in real time, i.e., in just a few milliseconds per frame. In this proposal, we exploit the fact that dynamic point clouds captured in real time are often only relevant for display and interaction in the current frame and inside the current view frustum. In particular, we propose a new view-dependent data structure that permits efficient connectivity creation and traversal of unstructured data, which will speed up surface recovery, e.g. for collision detection. Classifying occlusions comes at no extra cost, which will allow quick access to occluded layers in the current view. This enables new methods to explore and manipulate dynamic 3D scenes, overcoming interaction methods that rely on physics-based metaphors like walking or flying, lifting interaction with 3D environments to a “superhuman” level.</p>\r\n",
                "abstract": "<p>In recent years, virtual and augmented reality have gained widespread attention because of newly developed head-mounted displays. For the first time, mass-market penetration seems plausible. Also, range sensors are on the verge of being integrated into smartphones, evidenced by prototypes such as the Google Tango device, making ubiquitous on-line acquisition of 3D data a possibility. The combination of these two technologies – displays and sensors – promises applications where users can directly be immersed into an experience of 3D data that was just captured live. However, the captured data needs to be processed and structured before being displayed. For example, sensor noise needs to be removed, normals need to be estimated for local surface reconstruction, etc. The challenge is that these operations involve a large amount of data, and in order to ensure a lag-free user experience, they need to be performed in real time, i.e., in just a few milliseconds per frame. In this proposal, we exploit the fact that dynamic point clouds captured in real time are often only relevant for display and interaction in the current frame and inside the current view frustum. In particular, we propose a new view-dependent data structure that permits efficient connectivity creation and traversal of unstructured data, which will speed up surface recovery, e.g. for collision detection. Classifying occlusions comes at no extra cost, which will allow quick access to occluded layers in the current view. This enables new methods to explore and manipulate dynamic 3D scenes, overcoming interaction methods that rely on physics-based metaphors like walking or flying, lifting interaction with 3D environments to a “superhuman” level.</p>\r\n",
                "start_date": "2019-09-01",
                "end_date": "2023-08-31",
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                        "id": "fwf",
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                        "comment": "332.780,70 €"
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                ],
                "research_areas": [
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                    "VR"
                ],
                "publications": [
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                    "erler_philipp-2017-phd",
                    "erler-2020-p2s",
                    "leimer_2020-cag",
                    "marin-2024-pcp",
                    "parakkat-2024-ballmerge",
                    "rait_alexius-2021-baa",
                    "SCHUETZ-2020-MPC",
                    "schuetz-2020-PPC"
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            {
                "id": "MAKE-IT-FAB",
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                "drupal_id": 4185,
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                "name": "MAKE-IT-FAB: Modeling of Shapes for Personal Fabrication",
                "name_de": null,
                "short_title": "MAKE-IT-FAB",
                "website": null,
                "status": "active",
                "short_abstract": "The aim of this project is to investigate and to contribute to shape modeling and geometry processing for personal fabrication---a trend that currently receives intensified attention in the science and industry. Our goal is to contribute novel algorithmic solutions for fabrication-aware shape processing and interactive modeling. ",
                "abstract": "The aim of this project is to investigate and to contribute to shape modeling and geometry processing for personal fabrication---a trend that currently receives intensified attention in the science and industry. \nOur goal is to contribute novel algorithmic solutions for fabrication-aware shape processing and interactive modeling. In particular, we want to research following aspects: (i) We want to address the currently pending problem of high-level shape understanding, (ii) we want to research novel high-level shape modeling methods for interactive creation of plausible and aesthetically appealing shapes, and finally, (iii) we want to address optimization problems related to instant desktop 3D printing, such that modeled objects can be directly fabricated. The outcome of the project will be a set of algorithmic solutions for high-level shape modeling for instant personal fabrication.",
                "start_date": "2015-04-01",
                "end_date": "2020-03-31",
                "leader_id": 844,
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                        "id": "fwf",
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                        "comment": null
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                "research_areas": [
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                ],
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                    "birsak-2017-dpe",
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                    "Birsak2018-SA",
                    "erler-2020-p2s",
                    "gersthofer-2016-sosob",
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                    "hafner-2015-onff",
                    "leimer_2017_rbpesc",
                    "leimer_2020-cag",
                    "leimer-2016-coan",
                    "leimer-2016-rpe",
                    "leimer-2018-sar",
                    "musialski_2016_sosp",
                    "musialski-2015-ista",
                    "musialski-2015-pixel",
                    "musialski-2015-souos",
                    "musialski-2015-vrvis",
                    "steiner_2016_isad",
                    "WINKLER-2019-PDG"
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                "url": "https://www.cg.tuwien.ac.at/research/projects/MAKE-IT-FAB",
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            {
                "id": "geo-materials",
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                "name": "Computational Design of Geometric Materials",
                "name_de": null,
                "short_title": "geo-materials",
                "website": null,
                "status": "active",
                "short_abstract": "In this project we want to research novel materials whose mechanical behavior is described by the complexity of their geometry. Such “geometric materials” are cellular structures whose properties depend on the shape and the connectivity of their cells, while the actual physical substance they are built of is constant across the entire object. ",
                "abstract": "<p>In this project we want to research novel materials whose mechanical behavior is described by the complexity of their geometry. Such “geometric materials” are cellular structures whose properties depend on the shape and the connectivity of their cells, while the actual physical substance they are built of is constant across the entire object. Our goal is to develop the first computational model for the analysis and simulation of complex geometric materials, as well as a so-called goal-based computational design framework for their synthesis. Goal-based means that the desired behavior can be specified a-priori by the designer, and an appropriate geometric structure that best approximates the given goals is computed automatically. Our main research problem is how to map mechanical properties to geometric connections of cellular structures.</p>\r\n",
                "start_date": "2016-03-01",
                "end_date": "2021-08-31",
                "leader_id": 844,
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                "funding_organisations": [
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                        "id": "WWTF",
                        "contract_number": null,
                        "comment": null
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                    "leimer-2018-sar"
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    {
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        "type_id": "masterthesis",
        "tu_id": null,
        "repositum_id": null,
        "title": "Pose-Driven Generation and Optimization of Seating Furniture",
        "date": "2019-10-21",
        "abstract": "Modern furniture design systems provide seating solutions for various applications,\nranging from general purpose solutions to specific environments. The central goal of\nfurniture design is to create comfortable seating surfaces. To provide optimal comfort for\na specific person and environment, personalized furniture design is required. As comfort\nis generally seen as the user’s subjective feeling, objective comfort measures are defined\nthat approximate a person’s comfort for a given seating surface. Computational furniture\ndesign systems create seating solutions for a given scenario using interactive algorithms.\nSpecialized seating surfaces often require extensive manual design effort.\nIn this thesis, a computational furniture design framework to generate personalized\nseating surfaces is proposed. Utilizing a notation of sitting comfort based on equal\npressure distribution, our algorithm generates seating surface models fitted to a person\nin a specific pose. We introduce an automated furniture design framework able to create\ncomfortable seating surfaces for specific body shapes and poses. We developed a generic\ntemplate model capable of supporting a large variety of sitting poses and human body\nshapes that is matched to an input pose in multi stage fitting process. Furthermore, we\nintroduce a non-linear mesh optimization algorithm for further functional and visual\nimprovements.\nIn addition, the proposed framework serves as a fully automated solution to create\nspecialized control meshes usable as input meshes in other design frameworks, thus\neliminating the need for manual design effort.",
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        "authors": [
            {
                "id": 1422,
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                "firstname": "Andreas",
                "lastname": "Winkler",
                "searchname": "Andreas Winkler",
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                "name": "Andreas Winkler",
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        "date_end": "2019-10-21",
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        "diploma_examina": "2020-01-22",
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                "website": "https://www.cg.tuwien.ac.at/staff/KurtLeimer",
                "firstname": "Kurt",
                "lastname": "Leimer",
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                    "leimer_2020-cag",
                    "leimer-2013-esopc",
                    "leimer-2014-fsco",
                    "leimer-2016-coan",
                    "leimer-2016-rpe",
                    "leimer-2018-sar",
                    "leimer-2023-ecd"
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            {
                "id": "Fabrication",
                "drupal_id": 4132,
                "name": "Fabrication",
                "short_abstract": "The advent of consumer-grade 3D printing has recently sparked interest in fabrication-aware shape design and optimization. We use techniques from computer graphics and engineering to develop new computational tools to facilitate the design process of physical artifacts.",
                "abstract": "The task of finding the perfect shape of a real-world object that fulfills a given objective optimally appears in many disciplines, like interior design, building planning, or construction of machine parts. These tasks can be subject to considerations of functionality, cost-effciency, and aesthetics, as well as constraints relating to size, producibility, safety margins, etc. The great complexity and the presence of conflicting and hard-to-formalize goals have hitherto precluded automation of many design tasks and leave them in the hands of human designers and engineers.\n\nThere is, however, great potential to aid these processes computationally and to unlock difficult design tasks for a larger audience. This will not only provide faster work flows and enable the exploration of new design spaces, but it constitutes a necessary step towards the wide-spread application of personalized fabrication techniques like additive manufacturing. Low-cost 3d printing has been widely described as a disruptive technology and the herald of a new industrial revolution. These expectations have since been tempered by a reality which shows that availability alone is inconsequential unless accompanied by an innovation of supporting technologies.\n\nThe big challenge in making new fabrication techniques more useful is the development of a computational design methodology that relieves its users of low-level tasks like explicit 3d modeling and provides tools to create shapes from functional, aesthetic, and other high-level specifications. The overarching goal of this research area is to find new mathematical models and computational solutions fordesign tasks that are at this time tedious or impossible at all.",
                "website": "https://www.cg.tuwien.ac.at/research/area/Fabrication",
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                    "gersthofer-2016-sosob",
                    "hafner-2015-eigf",
                    "hafner-2015-onff",
                    "korpitsch_thorsten-2019",
                    "korpitsch-2020-cescg",
                    "leimer_2020-cag",
                    "leimer-2018-sar",
                    "musialski_2016_sosp",
                    "musialski-2015-souos",
                    "pahr-2021-vologram",
                    "pahr-2024-squishicalization",
                    "Reichinger-2016-spaghetti",
                    "schindler_2020vis",
                    "schultes_lampi",
                    "Staudacher_2022",
                    "walchhofer-tso",
                    "WINKLER-2019-PDG"
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                "projects": [
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                    "MAKE-IT-FAB"
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                "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Fabrication",
                "__class": "ResearchArea"
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                "id": "Geometry",
                "drupal_id": 4129,
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                "short_abstract": "Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.",
                "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ",
                "website": "https://www.cg.tuwien.ac.at/research/area/Geometry",
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                    "ausserer-2026-baa",
                    "balvan-rsf",
                    "bayer_bernhard-2026-baa",
                    "beleznai_csaba-2025-pr",
                    "belic_dejan_pr",
                    "bodzenta-2026-baa",
                    "brunner_lukas_2022_ssb",
                    "celarek-2022-gmcn",
                    "clemenz_2019_rosy_fields",
                    "cornel-2022-wih",
                    "csecsy-fcd",
                    "darovskikh_leonid-2025-prj",
                    "deak-a3",
                    "depner_dennis-2020-baa",
                    "depner_dennis-2022-maa",
                    "Doerflinger-2016-CDV",
                    "elagrod_ahmed-baa",
                    "Erhardt_2025_Scutes",
                    "erler_2024_ppsurf",
                    "erler_philipp-2017-phd",
                    "erler-2020-p2s",
                    "erler-2025-lidarscout",
                    "fitzinger_andreas-daa",
                    "forsythe-2016-ccm",
                    "fraissl_niklas-2023-pra",
                    "fuchs_peter-2024-baa",
                    "fuericht_2025_prj",
                    "fuericht_elias-2025-prj",
                    "gamsjaeger-2022-proc",
                    "gersthofer-2016-sosob",
                    "geyer_lukas_2015_prj",
                    "Grossfurtner-2023-paego",
                    "grossmann-2016-baa",
                    "gruber_horst-2019-baa",
                    "Guerrero-2014-TPS",
                    "hamzic_ademir-baa",
                    "harisch-mvs",
                    "hatzinger-2026-baa",
                    "hladky-2022-QS",
                    "hofer_kerstin-2023-sketch2model",
                    "hoffer-toth-com",
                    "holom_2025-prj",
                    "ILCIK-phdthesis",
                    "jira_marcel-2024-baa",
                    "kaipel_nikolas-2025-baa",
                    "kapferer_2021_advancing",
                    "kazda-tmd",
                    "Kellner-2021-DA",
                    "kerbl-2022-trienc",
                    "koeppel-2016-baa",
                    "kohlhas_jakob-2023-pra",
                    "konrad-2020-baa",
                    "kozonits_marcel-2025-baa",
                    "kralicek_sebastian_baa",
                    "kubicek-2024-baa",
                    "Kugler_2019",
                    "laager_florian-2014-daa",
                    "lang_jakob-2022-baa",
                    "Laschober-2018",
                    "lazarevic-tci",
                    "leimer_2017_rbpesc",
                    "leimer_2020-cag",
                    "leimer-2016-rpe",
                    "leimer-2018-sar",
                    "leutschacher_2025_prj",
                    "loeffelmann-1995-para",
                    "machacek_christian-2026-prj",
                    "macho_jonas-2024-baa",
                    "marin-2022-sig",
                    "marin-2022-sigdt",
                    "marin-2023-pic",
                    "marin-2024-pcp",
                    "marin-2024-sing",
                    "markovich_aleksandar-2022-maa",
                    "mayer_luiz-2026-baa",
                    "mayr_patrick_maa",
                    "Mayrhauser-2016-Cnc",
                    "mazza-2012-bakk",
                    "micu_2025-prj",
                    "miklautsch_florian-baa",
                    "mueller-2024-rbt",
                    "mujadzic_iman_baa",
                    "mujadzic-2023-hfp",
                    "murturi_PGG",
                    "musialski_2016_sosp",
                    "musialski-2012-sur",
                    "musialski-2013-surcgf",
                    "nawrocki-2024-nsr",
                    "negi_ashish-2023-baa",
                    "neumann-sfd",
                    "novak_martin-2018-baa",
                    "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-2019-xms",
                    "ohrhallinger_stefan-2022-tut",
                    "ohrhallinger_stefan-2023-con",
                    "ohrhallinger_stefan-2024-inv",
                    "ohrhallinger-2016-sgp",
                    "ohrhallinger-2021-egs",
                    "ohrhallinger-stefan-2012-the",
                    "pakkanen-2026-prj",
                    "pegrisch_2018_uvs",
                    "perzi_marvin-2026-baa",
                    "pichler_2022_fro",
                    "pointner_michael-2017-baa",
                    "pointner_simon-2022-maa",
                    "preiner_2012_AS",
                    "preiner_2017_phd",
                    "Preiner_2019",
                    "preiner2014clop",
                    "proelss-bdp",
                    "prohaska_julia-2023-baa",
                    "Radwan-2014-CDR",
                    "Radwan-2017-Occ",
                    "radwan-thesis",
                    "rait_alexius-2021-baa",
                    "REICHHOLF-2023-HRO",
                    "reiher_joerg-2023-pra",
                    "reiher-joerg-2024-daa",
                    "reinwald-2017-baa",
                    "Reisner_2013_RSB",
                    "resch_martin-2026-baa",
                    "riegler_2020_framework",
                    "roth_vdi",
                    "rozanics-lsf",
                    "rubik_michael-2022-baa",
                    "rumpelnik_martin_2020_PRM",
                    "schaffarz_2018-pra",
                    "schartmueller_2018_baa",
                    "Scheiblauer-2008-DCW",
                    "SCHEIBLAUER-2009-IDCE",
                    "scheiblauer-2011-cag",
                    "scheiblauer-2011-chnt",
                    "scheiblauer-2012-chnt",
                    "scheiblauer-2013-wscg",
                    "Schmalstieg-1996-LOB",
                    "Schmalstieg-1997-SMO",
                    "scholz_2017_bac",
                    "schrammel_sebastian_baa",
                    "SCHUETZ-2022-PCC",
                    "schuh-2018-mesh-blending",
                    "schulz-faf",
                    "seisenbacher-cyclesafely",
                    "sippl-2014-fss",
                    "slajcho_levente-baa",
                    "slavtchev-dcd",
                    "starnberger-cli",
                    "steiner_2016_isad",
                    "steinheber-2024-oto",
                    "steinschauer-2020-baa",
                    "steinschorn-2023-p2m",
                    "steinschorn-2025-par",
                    "Tobler-1995-AAC",
                    "Tobler-1995-BGD",
                    "tobler02_amrmg",
                    "Traxler-1996-CTB",
                    "trenovatz-lpd",
                    "tumpach_barbara-pra",
                    "unterguggenberger-2021-msh",
                    "Vucenovic_2022",
                    "wagentristl_stefan-2026-baa",
                    "WEYDEMANN-2016-NUO",
                    "weydemann-2025-noo",
                    "wiesinger_2025-baa",
                    "wiesinger_klemens-2023-baa",
                    "Wimmer-1998-SMO",
                    "WIMMER-2006-DWN",
                    "WIMMER-2006-IP",
                    "WIMMER-2016-HARVEST4D",
                    "withalm_brigitte-2022-baa",
                    "wolffhardt-2026-prj",
                    "yoo-chaeran-2025-pr",
                    "zeilinger_matthias-2020-baa",
                    "Zezulka-2024-FTS"
                ],
                "projects": [
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                    "d4388",
                    "d9275",
                    "EVOCATION",
                    "GameTools",
                    "Harvest4D",
                    "SCI_BIM",
                    "ShapeAcquisition",
                    "Superhumans",
                    "TERAPOINTS",
                    "WorldScale"
                ],
                "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry",
                "__class": "ResearchArea"
            },
            {
                "id": "Modeling",
                "drupal_id": 4130,
                "name": "Modeling",
                "short_abstract": "In this area, we focus on researching methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.",
                "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.",
                "website": "https://www.cg.tuwien.ac.at/research/area/Modeling",
                "teaser": {
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                    "type": "image/jpeg",
                    "size": 190581,
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                    "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Modeling/teaser:thumb{{size}}.png",
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                "workgroups": [
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                ],
                "publications": [
                    "AA2020",
                    "Adorjan-2015",
                    "aichner-2016-sadf",
                    "arikan-2013-osn",
                    "birsak-thesis",
                    "Birsak2018-SA",
                    "Brandstaetter2020",
                    "brunner_lukas_2022_ssb",
                    "Caic2021",
                    "clemenz_2019_rosy_fields",
                    "DOG10",
                    "dusberger-2010-msm",
                    "eibens-2021-tsgpmg",
                    "eibensteiner-2021-pmcg",
                    "eibner-2009-gpc",
                    "Erhardt_2025_Scutes",
                    "erler_2024_ppsurf",
                    "erler_philipp-2016-femfluid-prakt",
                    "erler_philipp-2017-phd",
                    "erler-2020-p2s",
                    "erler-2025-lidarscout",
                    "fan-2014-scfl",
                    "ferschin-1992-kons",
                    "fiedler-2009-php",
                    "fleiss-2015-da",
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                "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.",
                "website": "https://www.cg.tuwien.ac.at/research/area/Modeling",
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            {
                "id": "Photo-Guide",
                "workgroup_id": "rend",
                "drupal_id": 4218,
                "drupal_path": "/research/projects/Photo-Guide",
                "name": "Photo-Guide: Image-Based City Exploration",
                "name_de": null,
                "short_title": "Photo-Guide",
                "website": null,
                "status": "active",
                "short_abstract": "The core idea of the project is the enhancement of current state-of-the art navigation systems by visual information obtained from geo-referenced photographs. The aim is to establish a suite of tools together with  algorithmic foundations that will be essential for any large scale image-based guidance project.",
                "abstract": "<p>\nThe core idea of the project is the enhancement of current state-of-the art navigation systems by visual information obtained from geo-referenced photographs. The aim is to establish a suite of tools together with  algorithmic foundations that will be essential for any large scale image-based guidance project.\n\n<p>\nThe main hypothesis of this project is that in the case of guidance, especially for pedestrians, the first-person perspective is intuitive and leads to natural orientation. In the project we will  research how to generate first-person views on top of databases of simple ground-based photographs and classical overview maps. The ultimate idea is a system which allows the user to navigate through a city and even through interiors of buildings guided by the aid of annotated first-person views. Furthermore, the actual creation of the routes shall happen automatically on demand.\n\n<p>\nExamples of fields that can benefit from the proposed approach are tourism and general entertainment industries, city planners, local governments, simulation and security training, emergency management, civil protection and disaster control, as well as driving simulation to name but a few. Ultimately, the following scientific fields can profit from the proposed basic research results: computer graphics with image processing, computer vision, computational photography, pattern recognition, photogrammetry and remote sensing, cartography, computer aided design, geo-sciences and mobile-technology.",
                "start_date": "2011-01-01",
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                "abstract": "The task of finding the perfect shape of a real-world object that fulfills a given objective optimally appears in many disciplines, like interior design, building planning, or construction of machine parts. These tasks can be subject to considerations of functionality, cost-effciency, and aesthetics, as well as constraints relating to size, producibility, safety margins, etc. The great complexity and the presence of conflicting and hard-to-formalize goals have hitherto precluded automation of many design tasks and leave them in the hands of human designers and engineers.\n\nThere is, however, great potential to aid these processes computationally and to unlock difficult design tasks for a larger audience. This will not only provide faster work flows and enable the exploration of new design spaces, but it constitutes a necessary step towards the wide-spread application of personalized fabrication techniques like additive manufacturing. Low-cost 3d printing has been widely described as a disruptive technology and the herald of a new industrial revolution. These expectations have since been tempered by a reality which shows that availability alone is inconsequential unless accompanied by an innovation of supporting technologies.\n\nThe big challenge in making new fabrication techniques more useful is the development of a computational design methodology that relieves its users of low-level tasks like explicit 3d modeling and provides tools to create shapes from functional, aesthetic, and other high-level specifications. The overarching goal of this research area is to find new mathematical models and computational solutions fordesign tasks that are at this time tedious or impossible at all.",
                "website": "https://www.cg.tuwien.ac.at/research/area/Fabrication",
                "teaser": {
                    "name": "teaser.png",
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                "workgroups": [
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                ],
                "publications": [
                    "Birsak2018-SA",
                    "gersthofer-2016-sosob",
                    "hafner-2015-eigf",
                    "hafner-2015-onff",
                    "korpitsch_thorsten-2019",
                    "korpitsch-2020-cescg",
                    "leimer_2020-cag",
                    "leimer-2018-sar",
                    "musialski_2016_sosp",
                    "musialski-2015-souos",
                    "pahr-2021-vologram",
                    "pahr-2024-squishicalization",
                    "Reichinger-2016-spaghetti",
                    "schindler_2020vis",
                    "schultes_lampi",
                    "Staudacher_2022",
                    "walchhofer-tso",
                    "WINKLER-2019-PDG"
                ],
                "projects": [
                    "EVOCATION",
                    "MAKE-IT-FAB"
                ],
                "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Fabrication",
                "__class": "ResearchArea"
            },
            {
                "id": "Geometry",
                "drupal_id": 4129,
                "name": "Geometry Processing",
                "short_abstract": "Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.",
                "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ",
                "website": "https://www.cg.tuwien.ac.at/research/area/Geometry",
                "teaser": {
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                },
                "workgroups": [
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                ],
                "publications": [
                    "aichner-2016-sadf",
                    "arikan-2013-osn",
                    "ausserer-2026-baa",
                    "balvan-rsf",
                    "bayer_bernhard-2026-baa",
                    "beleznai_csaba-2025-pr",
                    "belic_dejan_pr",
                    "bodzenta-2026-baa",
                    "brunner_lukas_2022_ssb",
                    "celarek-2022-gmcn",
                    "clemenz_2019_rosy_fields",
                    "cornel-2022-wih",
                    "csecsy-fcd",
                    "darovskikh_leonid-2025-prj",
                    "deak-a3",
                    "depner_dennis-2020-baa",
                    "depner_dennis-2022-maa",
                    "Doerflinger-2016-CDV",
                    "elagrod_ahmed-baa",
                    "Erhardt_2025_Scutes",
                    "erler_2024_ppsurf",
                    "erler_philipp-2017-phd",
                    "erler-2020-p2s",
                    "erler-2025-lidarscout",
                    "fitzinger_andreas-daa",
                    "forsythe-2016-ccm",
                    "fraissl_niklas-2023-pra",
                    "fuchs_peter-2024-baa",
                    "fuericht_2025_prj",
                    "fuericht_elias-2025-prj",
                    "gamsjaeger-2022-proc",
                    "gersthofer-2016-sosob",
                    "geyer_lukas_2015_prj",
                    "Grossfurtner-2023-paego",
                    "grossmann-2016-baa",
                    "gruber_horst-2019-baa",
                    "Guerrero-2014-TPS",
                    "hamzic_ademir-baa",
                    "harisch-mvs",
                    "hatzinger-2026-baa",
                    "hladky-2022-QS",
                    "hofer_kerstin-2023-sketch2model",
                    "hoffer-toth-com",
                    "holom_2025-prj",
                    "ILCIK-phdthesis",
                    "jira_marcel-2024-baa",
                    "kaipel_nikolas-2025-baa",
                    "kapferer_2021_advancing",
                    "kazda-tmd",
                    "Kellner-2021-DA",
                    "kerbl-2022-trienc",
                    "koeppel-2016-baa",
                    "kohlhas_jakob-2023-pra",
                    "konrad-2020-baa",
                    "kozonits_marcel-2025-baa",
                    "kralicek_sebastian_baa",
                    "kubicek-2024-baa",
                    "Kugler_2019",
                    "laager_florian-2014-daa",
                    "lang_jakob-2022-baa",
                    "Laschober-2018",
                    "lazarevic-tci",
                    "leimer_2017_rbpesc",
                    "leimer_2020-cag",
                    "leimer-2016-rpe",
                    "leimer-2018-sar",
                    "leutschacher_2025_prj",
                    "loeffelmann-1995-para",
                    "machacek_christian-2026-prj",
                    "macho_jonas-2024-baa",
                    "marin-2022-sig",
                    "marin-2022-sigdt",
                    "marin-2023-pic",
                    "marin-2024-pcp",
                    "marin-2024-sing",
                    "markovich_aleksandar-2022-maa",
                    "mayer_luiz-2026-baa",
                    "mayr_patrick_maa",
                    "Mayrhauser-2016-Cnc",
                    "mazza-2012-bakk",
                    "micu_2025-prj",
                    "miklautsch_florian-baa",
                    "mueller-2024-rbt",
                    "mujadzic_iman_baa",
                    "mujadzic-2023-hfp",
                    "murturi_PGG",
                    "musialski_2016_sosp",
                    "musialski-2012-sur",
                    "musialski-2013-surcgf",
                    "nawrocki-2024-nsr",
                    "negi_ashish-2023-baa",
                    "neumann-sfd",
                    "novak_martin-2018-baa",
                    "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-2019-xms",
                    "ohrhallinger_stefan-2022-tut",
                    "ohrhallinger_stefan-2023-con",
                    "ohrhallinger_stefan-2024-inv",
                    "ohrhallinger-2016-sgp",
                    "ohrhallinger-2021-egs",
                    "ohrhallinger-stefan-2012-the",
                    "pakkanen-2026-prj",
                    "pegrisch_2018_uvs",
                    "perzi_marvin-2026-baa",
                    "pichler_2022_fro",
                    "pointner_michael-2017-baa",
                    "pointner_simon-2022-maa",
                    "preiner_2012_AS",
                    "preiner_2017_phd",
                    "Preiner_2019",
                    "preiner2014clop",
                    "proelss-bdp",
                    "prohaska_julia-2023-baa",
                    "Radwan-2014-CDR",
                    "Radwan-2017-Occ",
                    "radwan-thesis",
                    "rait_alexius-2021-baa",
                    "REICHHOLF-2023-HRO",
                    "reiher_joerg-2023-pra",
                    "reiher-joerg-2024-daa",
                    "reinwald-2017-baa",
                    "Reisner_2013_RSB",
                    "resch_martin-2026-baa",
                    "riegler_2020_framework",
                    "roth_vdi",
                    "rozanics-lsf",
                    "rubik_michael-2022-baa",
                    "rumpelnik_martin_2020_PRM",
                    "schaffarz_2018-pra",
                    "schartmueller_2018_baa",
                    "Scheiblauer-2008-DCW",
                    "SCHEIBLAUER-2009-IDCE",
                    "scheiblauer-2011-cag",
                    "scheiblauer-2011-chnt",
                    "scheiblauer-2012-chnt",
                    "scheiblauer-2013-wscg",
                    "Schmalstieg-1996-LOB",
                    "Schmalstieg-1997-SMO",
                    "scholz_2017_bac",
                    "schrammel_sebastian_baa",
                    "SCHUETZ-2022-PCC",
                    "schuh-2018-mesh-blending",
                    "schulz-faf",
                    "seisenbacher-cyclesafely",
                    "sippl-2014-fss",
                    "slajcho_levente-baa",
                    "slavtchev-dcd",
                    "starnberger-cli",
                    "steiner_2016_isad",
                    "steinheber-2024-oto",
                    "steinschauer-2020-baa",
                    "steinschorn-2023-p2m",
                    "steinschorn-2025-par",
                    "Tobler-1995-AAC",
                    "Tobler-1995-BGD",
                    "tobler02_amrmg",
                    "Traxler-1996-CTB",
                    "trenovatz-lpd",
                    "tumpach_barbara-pra",
                    "unterguggenberger-2021-msh",
                    "Vucenovic_2022",
                    "wagentristl_stefan-2026-baa",
                    "WEYDEMANN-2016-NUO",
                    "weydemann-2025-noo",
                    "wiesinger_2025-baa",
                    "wiesinger_klemens-2023-baa",
                    "Wimmer-1998-SMO",
                    "WIMMER-2006-DWN",
                    "WIMMER-2006-IP",
                    "WIMMER-2016-HARVEST4D",
                    "withalm_brigitte-2022-baa",
                    "wolffhardt-2026-prj",
                    "yoo-chaeran-2025-pr",
                    "zeilinger_matthias-2020-baa",
                    "Zezulka-2024-FTS"
                ],
                "projects": [
                    "3DSpatialization",
                    "d4388",
                    "d9275",
                    "EVOCATION",
                    "GameTools",
                    "Harvest4D",
                    "SCI_BIM",
                    "ShapeAcquisition",
                    "Superhumans",
                    "TERAPOINTS",
                    "WorldScale"
                ],
                "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Geometry",
                "__class": "ResearchArea"
            },
            {
                "id": "Modeling",
                "drupal_id": 4130,
                "name": "Modeling",
                "short_abstract": "In this area, we focus on researching methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.",
                "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.",
                "website": "https://www.cg.tuwien.ac.at/research/area/Modeling",
                "teaser": {
                    "name": "teaser.jpg",
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                },
                "workgroups": [
                    "rend"
                ],
                "publications": [
                    "AA2020",
                    "Adorjan-2015",
                    "aichner-2016-sadf",
                    "arikan-2013-osn",
                    "birsak-thesis",
                    "Birsak2018-SA",
                    "Brandstaetter2020",
                    "brunner_lukas_2022_ssb",
                    "Caic2021",
                    "clemenz_2019_rosy_fields",
                    "DOG10",
                    "dusberger-2010-msm",
                    "eibens-2021-tsgpmg",
                    "eibensteiner-2021-pmcg",
                    "eibner-2009-gpc",
                    "Erhardt_2025_Scutes",
                    "erler_2024_ppsurf",
                    "erler_philipp-2016-femfluid-prakt",
                    "erler_philipp-2017-phd",
                    "erler-2020-p2s",
                    "erler-2025-lidarscout",
                    "fan-2014-scfl",
                    "ferschin-1992-kons",
                    "fiedler-2009-php",
                    "fleiss-2015-da",
                    "GAHR-2013-AGM",
                    "gamsjaeger-2022-proc",
                    "gersthofer-2016-sosob",
                    "gervautz-1989-sol1",
                    "gervautz-1993-use",
                    "griessmair-1989-def1",
                    "groeller-1992-frac",
                    "groeller-1995-mod",
                    "Groeller-1995-SDC",
                    "Grossfurtner-2023-paego",
                    "Guerrero-2014-GRF",
                    "Guerrero-2014-TPS",
                    "guerrero-2015-lsp",
                    "HECHER-2017-HDY",
                    "hiess-1992-comb",
                    "hofer_kerstin-2023-sketch2model",
                    "honic-2020-w78",
                    "HU-2017-ETM",
                    "HUMMEL-2001-MSE",
                    "Ilcik_2015_LAY",
                    "ilcik-2010-ps",
                    "ilcik-2013-cipmi",
                    "ilcik-2014-cgbpmi",
                    "ilcik-2016-cmssg",
                    "ilcik-2021-xmas",
                    "kapferer_2021_advancing",
                    "karnik-09-shapegrammar",
                    "Kellner-2021-DA",
                    "kendlbacher-2016",
                    "klein_2019_PGG",
                    "klein_2019_PHD",
                    "klein_2019_PMP",
                    "koenigsberger-2024-msu",
                    "komon-2025-webigeo",
                    "kouril-2015-maya2cellview",
                    "kouril-2017-sccgposter",
                    "kraehsmaier-dsc",
                    "kreuzer-2016-isf",
                    "kuehtreiber-2010-ikph",
                    "leimer_2017_rbpesc",
                    "leimer_2020-cag",
                    "leimer-2016-coan",
                    "leimer-2016-rpe",
                    "leimer-2018-sar",
                    "leimer-2023-ecd",
                    "LEOPOLD-2017-ALG",
                    "LIPP-2007-CGA",
                    "LIPP-2008-IEV",
                    "LIPP-2009-PGL",
                    "LIPP-2009-PGL2",
                    "lipp2011a",
                    "Lupu-2026-Cloth",
                    "macho_jonas-2024-baa",
                    "Maierhofer-thesis",
                    "manpreet_kainth-2012-rus",
                    "miao_kaust_2018",
                    "miao_nantech_2019",
                    "miao_nar_2020",
                    "miao_thesis_2019",
                    "mindek-xmas-card-2016",
                    "mujadzic-2023-hfp",
                    "musialski-2009-sbfr",
                    "musialski-2010-pfi",
                    "musialski-2010-tof",
                    "musialski-2012-icb",
                    "musialski-2012-sur",
                    "Musialski-2013-ipmum",
                    "musialski-2013-surcgf",
                    "NIEDERREITER-2010-SIM",
                    "Pahr2020",
                    "Parzer_2013_IIG",
                    "pegrisch_2018_uvs",
                    "Pel-2026",
                    "pogrzebacz-2014-gggm",
                    "polzer-sog",
                    "preiner_2017_phd",
                    "PUEYO-2019-SCL",
                    "RADAX-2010-LOD",
                    "Radwan_2021_Occ",
                    "rasch-2016-imgses",
                    "recheis-2009-arr",
                    "Reichinger-12",
                    "reisinger-2023-iad",
                    "reisner-2010-ind",
                    "reisner-2011-akgeo",
                    "reitsamer-2008-tsud",
                    "Rumpelnik_Martin-2020-NPR",
                    "scharl-master-thesis",
                    "schneider-sturm-2026-mia",
                    "scholz_2017_bac",
                    "SCHWAERZLER-2017-SBGM",
                    "SIETZEN-2017-BBO",
                    "sifuentes-2018-crowd",
                    "sippl-2014-fss",
                    "sperl-2013-BA",
                    "spitaler-2015-pbi",
                    "steiner_2016_isad",
                    "steiner-2014-da",
                    "steinkellner-2022-dll",
                    "steinschorn-2023-p2m",
                    "steinschorn-2025-par",
                    "steinschorn-2025-parameter",
                    "tobler02_amrmg",
                    "tobler02_mbpls",
                    "Traxler-1996-GAI",
                    "VASILJEVS-2018-PMPL",
                    "Viola_Ivan_2013_RMA",
                    "Viola_Ivan_2013_RSb",
                    "weiner_2011",
                    "WIMMER-2015-CGFC",
                    "WIMMER-2016-FUTURIS",
                    "WIMMER-2020-ASG",
                    "wimmer-2023-acd",
                    "Winkler-2017",
                    "WINKLER-2019-PDG",
                    "Wonka-2003-Ins",
                    "xmas-2024",
                    "zeiller-1993-coll",
                    "Zotti-2003-AMP",
                    "zotti-2003-ash",
                    "zotti-2006-pla",
                    "zotti-2007-eg"
                ],
                "projects": [
                    "3DSpatialization",
                    "d4388",
                    "EVOCATION",
                    "GAMEWORLD",
                    "Harvest4D",
                    "PAMINA",
                    "Photo-Guide",
                    "REPLICATE",
                    "SCI_BIM",
                    "Wohnen 4.0"
                ],
                "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Modeling",
                "__class": "ResearchArea"
            }
        ],
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            "shape optimization",
            "blender plugin"
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        "projects_workgroups": [
            {
                "id": "MAKE-IT-FAB",
                "workgroup_id": "rend",
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                "name": "MAKE-IT-FAB: Modeling of Shapes for Personal Fabrication",
                "name_de": null,
                "short_title": "MAKE-IT-FAB",
                "website": null,
                "status": "active",
                "short_abstract": "The aim of this project is to investigate and to contribute to shape modeling and geometry processing for personal fabrication---a trend that currently receives intensified attention in the science and industry. Our goal is to contribute novel algorithmic solutions for fabrication-aware shape processing and interactive modeling. ",
                "abstract": "The aim of this project is to investigate and to contribute to shape modeling and geometry processing for personal fabrication---a trend that currently receives intensified attention in the science and industry. \nOur goal is to contribute novel algorithmic solutions for fabrication-aware shape processing and interactive modeling. In particular, we want to research following aspects: (i) We want to address the currently pending problem of high-level shape understanding, (ii) we want to research novel high-level shape modeling methods for interactive creation of plausible and aesthetically appealing shapes, and finally, (iii) we want to address optimization problems related to instant desktop 3D printing, such that modeled objects can be directly fabricated. The outcome of the project will be a set of algorithmic solutions for high-level shape modeling for instant personal fabrication.",
                "start_date": "2015-04-01",
                "end_date": "2020-03-31",
                "leader_id": 844,
                "logo": {
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                "funding_organisations": [
                    {
                        "id": "fwf",
                        "contract_number": "P27972-N31",
                        "comment": null
                    }
                ],
                "research_areas": [
                    "Fabrication"
                ],
                "publications": [
                    "aichner-2016-sadf",
                    "birsak-2017-dpe",
                    "birsak-thesis",
                    "Birsak2018-SA",
                    "erler-2020-p2s",
                    "gersthofer-2016-sosob",
                    "hafner-2015-eigf",
                    "hafner-2015-onff",
                    "leimer_2017_rbpesc",
                    "leimer_2020-cag",
                    "leimer-2016-coan",
                    "leimer-2016-rpe",
                    "leimer-2018-sar",
                    "musialski_2016_sosp",
                    "musialski-2015-ista",
                    "musialski-2015-pixel",
                    "musialski-2015-souos",
                    "musialski-2015-vrvis",
                    "steiner_2016_isad",
                    "WINKLER-2019-PDG"
                ],
                "url": "https://www.cg.tuwien.ac.at/research/projects/MAKE-IT-FAB",
                "__class": "Project"
            }
        ],
        "url": "https://www.cg.tuwien.ac.at/research/publications/2018/gersthofer-2016-sosob/",
        "__class": "Publication"
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        "doi": "10.1111/cgf.12996",
        "issn": "1467-8659",
        "journal": "Computer Graphics Forum",
        "lecturer": [
            {
                "id": 1120,
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                "website": "https://www.cg.tuwien.ac.at/staff/BernhardSteiner",
                "firstname": "Bernhard",
                "lastname": "Steiner",
                "searchname": "Bernhard Steiner",
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                "name": "Bernhard Steiner",
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                    "steiner-2014-da"
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                ],
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        "number": "8",
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        "volume": "36",
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                "id": "Geometry",
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                "name": "Geometry Processing",
                "short_abstract": "Uses concepts from applied mathematics and computer science to design efficient algorithms for the reconstruction, analysis, manipulation, simulation and transmission of complex 3D models. Example applications are collision detection, reconstruction, compression, occlusion-aware surface handling and improved sampling conditions.",
                "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ",
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                "abstract": "We perform research in surface reconstruction from point clouds, geometry processing and geometry representations. We use parallel processing of thousands of GPU cores to enable flash geometry operations in real-time.\nNovel data structures are evaluated to reduce the time complexity of geometric operations, such as collision detection or occlusion-aware surface processing.\nIn computational geometry, we prove concepts relating samples to curves and manifolds. We also research novel surface description paradigms and according operators, representing large point cloud data in a probabilistic way. ",
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                    "EVOCATION",
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                "short_abstract": "In this area, we focus on researching methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.",
                "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.",
                "website": "https://www.cg.tuwien.ac.at/research/area/Modeling",
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                    "clemenz_2019_rosy_fields",
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                    "erler-2025-lidarscout",
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                "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.",
                "website": "https://www.cg.tuwien.ac.at/research/area/Modeling",
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                    "eibensteiner-2021-pmcg",
                    "eibner-2009-gpc",
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                    "erler_2024_ppsurf",
                    "erler_philipp-2016-femfluid-prakt",
                    "erler_philipp-2017-phd",
                    "erler-2020-p2s",
                    "erler-2025-lidarscout",
                    "fan-2014-scfl",
                    "ferschin-1992-kons",
                    "fiedler-2009-php",
                    "fleiss-2015-da",
                    "GAHR-2013-AGM",
                    "gamsjaeger-2022-proc",
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                    "gervautz-1993-use",
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                    "groeller-1995-mod",
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                    "Grossfurtner-2023-paego",
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                    "HECHER-2017-HDY",
                    "hiess-1992-comb",
                    "hofer_kerstin-2023-sketch2model",
                    "honic-2020-w78",
                    "HU-2017-ETM",
                    "HUMMEL-2001-MSE",
                    "Ilcik_2015_LAY",
                    "ilcik-2010-ps",
                    "ilcik-2013-cipmi",
                    "ilcik-2014-cgbpmi",
                    "ilcik-2016-cmssg",
                    "ilcik-2021-xmas",
                    "kapferer_2021_advancing",
                    "karnik-09-shapegrammar",
                    "Kellner-2021-DA",
                    "kendlbacher-2016",
                    "klein_2019_PGG",
                    "klein_2019_PHD",
                    "klein_2019_PMP",
                    "koenigsberger-2024-msu",
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                    "LIPP-2008-IEV",
                    "LIPP-2009-PGL",
                    "LIPP-2009-PGL2",
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                    "steinkellner-2022-dll",
                    "steinschorn-2023-p2m",
                    "steinschorn-2025-par",
                    "steinschorn-2025-parameter",
                    "tobler02_amrmg",
                    "tobler02_mbpls",
                    "Traxler-1996-GAI",
                    "VASILJEVS-2018-PMPL",
                    "Viola_Ivan_2013_RMA",
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                    "Wonka-2003-Ins",
                    "xmas-2024",
                    "zeiller-1993-coll",
                    "Zotti-2003-AMP",
                    "zotti-2003-ash",
                    "zotti-2006-pla",
                    "zotti-2007-eg"
                ],
                "projects": [
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                    "d4388",
                    "EVOCATION",
                    "GAMEWORLD",
                    "Harvest4D",
                    "PAMINA",
                    "Photo-Guide",
                    "REPLICATE",
                    "SCI_BIM",
                    "Wohnen 4.0"
                ],
                "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Modeling",
                "__class": "ResearchArea"
            }
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            "geometry processing",
            "shape modeling",
            "shape-aware deformation"
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            {
                "id": "MAKE-IT-FAB",
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                "name": "MAKE-IT-FAB: Modeling of Shapes for Personal Fabrication",
                "name_de": null,
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                "website": null,
                "status": "active",
                "short_abstract": "The aim of this project is to investigate and to contribute to shape modeling and geometry processing for personal fabrication---a trend that currently receives intensified attention in the science and industry. Our goal is to contribute novel algorithmic solutions for fabrication-aware shape processing and interactive modeling. ",
                "abstract": "The aim of this project is to investigate and to contribute to shape modeling and geometry processing for personal fabrication---a trend that currently receives intensified attention in the science and industry. \nOur goal is to contribute novel algorithmic solutions for fabrication-aware shape processing and interactive modeling. In particular, we want to research following aspects: (i) We want to address the currently pending problem of high-level shape understanding, (ii) we want to research novel high-level shape modeling methods for interactive creation of plausible and aesthetically appealing shapes, and finally, (iii) we want to address optimization problems related to instant desktop 3D printing, such that modeled objects can be directly fabricated. The outcome of the project will be a set of algorithmic solutions for high-level shape modeling for instant personal fabrication.",
                "start_date": "2015-04-01",
                "end_date": "2020-03-31",
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                        "id": "fwf",
                        "contract_number": "P27972-N31",
                        "comment": null
                    }
                ],
                "research_areas": [
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                ],
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                    "birsak-2017-dpe",
                    "birsak-thesis",
                    "Birsak2018-SA",
                    "erler-2020-p2s",
                    "gersthofer-2016-sosob",
                    "hafner-2015-eigf",
                    "hafner-2015-onff",
                    "leimer_2017_rbpesc",
                    "leimer_2020-cag",
                    "leimer-2016-coan",
                    "leimer-2016-rpe",
                    "leimer-2018-sar",
                    "musialski_2016_sosp",
                    "musialski-2015-ista",
                    "musialski-2015-pixel",
                    "musialski-2015-souos",
                    "musialski-2015-vrvis",
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        "title": "Relation-Based Parametrization and Exploration of Shape Collections",
        "date": "2016-07",
        "abstract": "With online repositories for 3D models like 3D Warehouse becoming more prevalent and growing ever larger, new possibilities have opened up for both experienced and inexperienced users alike. These large collections of shapes can provide inspiration for designers or make it possible to synthesize new shapes by combining different parts from already existing shapes, which can be both easy to learn and a fast way of creating new shapes.\n\nBut exploring large shape collections or searching for particular kinds of shapes can be difficult and time-consuming tasks as well, especially considering that online repositories are often disorganized. In our work, we propose a relation-based way to parametrize shape collections, allowing the user to explore the entire set of shapes by controlling a small number of parameters.",
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        "substitute": null,
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        "authors": [
            {
                "id": 1019,
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                "website": "https://www.cg.tuwien.ac.at/staff/KurtLeimer",
                "firstname": "Kurt",
                "lastname": "Leimer",
                "searchname": "Kurt Leimer",
                "is_teacher": false,
                "name": "Kurt Leimer",
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                    "leimer_2020-cag",
                    "leimer-2013-esopc",
                    "leimer-2014-fsco",
                    "leimer-2016-coan",
                    "leimer-2016-rpe",
                    "leimer-2018-sar",
                    "leimer-2023-ecd"
                ],
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                "website": "https://www.cg.tuwien.ac.at/staff/MichaelWimmer",
                "firstname": "Michael",
                "lastname": "Wimmer",
                "searchname": "Michael Wimmer",
                "is_teacher": true,
                "name": "Michael Wimmer",
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                    "arikan-2015-dmrt",
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                    "Artusi-2003-Del",
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                    "Auzinger_2013_SAR",
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                    "bernhard-2010-gph",
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                    "bernhard-2011-maicg",
                    "bernhard-2014-EFD",
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                    "CADIK-2006-IAQ",
                    "CADIK-2008-EHD",
                    "cardoso-2021-cost",
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                    "ecormier-nocca-2025-sls",
                    "eibens-2021-tsgpmg",
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                    "EISEMANN-2012-ERT",
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                    "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",
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                    "GIEGL-2007-FVS",
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                    "guerrero-2008-sli",
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                    "Guerrero-2014-TPS",
                    "guerrero-2015-lsp",
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                    "Habel_09_PGT",
                    "Habel_2007_IAG",
                    "Habel_2007_RTT",
                    "Habel_2012_PSP",
                    "Habel_LSN_2011",
                    "Habel-2010-EIN",
                    "hafner-2015-onff",
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                    "kerbl-2022-trienc",
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                    "knecht_martin_2012_RSMR",
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                    "Musialski-2013-ipmum",
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                    "ohrhallinger_stefan-2018-pg",
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                    "pistellato-2023-elp",
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                    "Radwan-2014-CDR",
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                    "rasoulzadeh-2023-ani",
                    "rasoulzadeh-2024-strokes2surface",
                    "rasoulzadeh-2025-archcomplete",
                    "reisinger-2023-iad",
                    "ROEGNER-2015-IBR",
                    "roth_vdi",
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                    "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",
                    "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",
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        "title": "Optimization of Natural Frequencies for Fabrication-Aware Shape Modeling",
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        "abstract": "Given a target shape and a target frequency, we automatically synthesize shapes that exhibit this frequency as part of their natural spectrum while resembling the target shape as closely as possible. We propose three shape parametrization methods that afford meaningful degrees of freedom in the design of instruments such as marimbas and bells. The design space is based on the representation of a solid as the volume enclosed by an outer surface and an inner offset surface. In order to evaluate the natural frequency spectrum of a solid, we employ finite element modal analysis and evaluate the suitability of different element types. We propose a fabrication method for the production of optimized instruments by an amateur craftsperson using sand or rubber molds. The efficiency of our method is demonstrated by the production of a simple tin bell and a more complicated bell in the shape of a rabbit. We achieve agreement with the predicted pitch frequencies of 2.8% and 6% respectively. These physical results are supplemented by a number of computational results that explore the optimization of harmonic ratios and the influence of mesh resolution and mesh smoothness on the accuracy of the finite element model.",
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                "short_title": "MAKE-IT-FAB",
                "website": null,
                "status": "active",
                "short_abstract": "The aim of this project is to investigate and to contribute to shape modeling and geometry processing for personal fabrication---a trend that currently receives intensified attention in the science and industry. Our goal is to contribute novel algorithmic solutions for fabrication-aware shape processing and interactive modeling. ",
                "abstract": "The aim of this project is to investigate and to contribute to shape modeling and geometry processing for personal fabrication---a trend that currently receives intensified attention in the science and industry. \nOur goal is to contribute novel algorithmic solutions for fabrication-aware shape processing and interactive modeling. In particular, we want to research following aspects: (i) We want to address the currently pending problem of high-level shape understanding, (ii) we want to research novel high-level shape modeling methods for interactive creation of plausible and aesthetically appealing shapes, and finally, (iii) we want to address optimization problems related to instant desktop 3D printing, such that modeled objects can be directly fabricated. The outcome of the project will be a set of algorithmic solutions for high-level shape modeling for instant personal fabrication.",
                "start_date": "2015-04-01",
                "end_date": "2020-03-31",
                "leader_id": 844,
                "logo": {
                    "name": "logo.jpg",
                    "path": "project:MAKE-IT-FAB",
                    "type": "image/jpeg",
                    "size": 80511,
                    "orig_name": "logo.jpg",
                    "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/MAKE-IT-FAB/logo:thumb{{size}}.png",
                    "thumb_image_sizes": [
                        120,
                        300
                    ]
                },
                "funding_organisations": [
                    {
                        "id": "fwf",
                        "contract_number": "P27972-N31",
                        "comment": null
                    }
                ],
                "research_areas": [
                    "Fabrication"
                ],
                "publications": [
                    "aichner-2016-sadf",
                    "birsak-2017-dpe",
                    "birsak-thesis",
                    "Birsak2018-SA",
                    "erler-2020-p2s",
                    "gersthofer-2016-sosob",
                    "hafner-2015-eigf",
                    "hafner-2015-onff",
                    "leimer_2017_rbpesc",
                    "leimer_2020-cag",
                    "leimer-2016-coan",
                    "leimer-2016-rpe",
                    "leimer-2018-sar",
                    "musialski_2016_sosp",
                    "musialski-2015-ista",
                    "musialski-2015-pixel",
                    "musialski-2015-souos",
                    "musialski-2015-vrvis",
                    "steiner_2016_isad",
                    "WINKLER-2019-PDG"
                ],
                "url": "https://www.cg.tuwien.ac.at/research/projects/MAKE-IT-FAB",
                "__class": "Project"
            }
        ],
        "url": "https://www.cg.tuwien.ac.at/research/publications/2015/musialski-2015-ista/",
        "__class": "Publication"
    }
]
