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PiGraphs: learning interaction snapshots from observations

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Matthias NießnerAuthors Info & Claims

SA '16: SIGGRAPH ASIA 2016 Virtual Reality meets Physical Reality: Modelling and Simulating Virtual Humans and Environments

Article No.: 5, Pages 1 - 2

https://doi.org/10.1145/2992138.2992147

Published: 28 November 2016 Publication History

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Abstract

Computer graphics has made great progress in enabling people to create visual content. However, we still face a big content creation bottleneck. In particular, designing 3D scenes and virtual character interactions within them is still a time---consuming task requiring expertise and much manual effort. A common theme in addressing the content creation challenge in various subfields of graphics has been to leverage data in order to build statistical methods for automated content generation.

References

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Savva, M., Chang, A. X., Hanrahan, P., Fisher, M., and Niessner, M. 2016. PiGraphs: Learning interaction snapshots from observations. ACM Trans. Graph. 35, 4, 139:1--139:12.

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Cited By

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Kim HHan SKwon PJoo H(2024)Beyond the Contact: Discovering Comprehensive Affordance for 3D Objects from Pre-trained 2D Diffusion ModelsComputer Vision – ECCV 202410.1007/978-3-031-72983-6_23(400-419)Online publication date: 29-Oct-2024
https://doi.org/10.1007/978-3-031-72983-6_23
Fu HCai BGao LZhang LWang JLi CZeng QSun CJia RZhao BZhang H(2021)3D-FRONT: 3D Furnished Rooms with layOuts and semaNTics2021 IEEE/CVF International Conference on Computer Vision (ICCV)10.1109/ICCV48922.2021.01075(10913-10922)Online publication date: Oct-2021
https://doi.org/10.1109/ICCV48922.2021.01075
Hassan MGhosh PTesch JTzionas DBlack M(2021)Populating 3D Scenes by Learning Human-Scene Interaction2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR46437.2021.01447(14703-14713)Online publication date: Jun-2021
https://doi.org/10.1109/CVPR46437.2021.01447
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Index Terms

PiGraphs: learning interaction snapshots from observations
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Spatial and physical reasoning
  2. Computer graphics

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Published In

SA '16: SIGGRAPH ASIA 2016 Virtual Reality meets Physical Reality: Modelling and Simulating Virtual Humans and Environments

November 2016

42 pages

ISBN:9781450345484

DOI:10.1145/2992138

Conference Chair:
Hui Huang
Shenzhen University, China

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 November 2016

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SA '16

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SIGGRAPH

SA '16: SIGGRAPH Asia 2016

December 5 - 8, 2016

Macau

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Overall Acceptance Rate 178 of 869 submissions, 20%

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Cited By

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Kim HHan SKwon PJoo H(2024)Beyond the Contact: Discovering Comprehensive Affordance for 3D Objects from Pre-trained 2D Diffusion ModelsComputer Vision – ECCV 202410.1007/978-3-031-72983-6_23(400-419)Online publication date: 29-Oct-2024
https://doi.org/10.1007/978-3-031-72983-6_23
Fu HCai BGao LZhang LWang JLi CZeng QSun CJia RZhao BZhang H(2021)3D-FRONT: 3D Furnished Rooms with layOuts and semaNTics2021 IEEE/CVF International Conference on Computer Vision (ICCV)10.1109/ICCV48922.2021.01075(10913-10922)Online publication date: Oct-2021
https://doi.org/10.1109/ICCV48922.2021.01075
Hassan MGhosh PTesch JTzionas DBlack M(2021)Populating 3D Scenes by Learning Human-Scene Interaction2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR46437.2021.01447(14703-14713)Online publication date: Jun-2021
https://doi.org/10.1109/CVPR46437.2021.01447
Liu MYang DZhang YCui ZRehg JTang S(2021)4D Human Body Capture from Egocentric Video via 3D Scene Grounding2021 International Conference on 3D Vision (3DV)10.1109/3DV53792.2021.00101(930-939)Online publication date: Dec-2021
https://doi.org/10.1109/3DV53792.2021.00101
Hu RSavva Mvan Kaick O(2020)Learning 3D functionality representationsSIGGRAPH Asia 2020 Courses10.1145/3415263.3419152(1-5)Online publication date: 17-Nov-2020
https://dl.acm.org/doi/10.1145/3415263.3419152
Pintore GMura CGanovelli FFuentes-Perez LPajarola RGobbetti E(2020)Automatic 3D reconstruction of structured indoor environmentsACM SIGGRAPH 2020 Courses10.1145/3388769.3407469(1-218)Online publication date: 17-Aug-2020
https://dl.acm.org/doi/10.1145/3388769.3407469
Cao ZGao HMangalam KCai QVo MMalik J(2020)Long-Term Human Motion Prediction with Scene ContextComputer Vision – ECCV 202010.1007/978-3-030-58452-8_23(387-404)Online publication date: 3-Nov-2020
https://doi.org/10.1007/978-3-030-58452-8_23
Monszpart AGuerrero PCeylan DYumer EMitra N(2019)iMapperACM Transactions on Graphics10.1145/3306346.332296138:4(1-15)Online publication date: 12-Jul-2019
https://dl.acm.org/doi/10.1145/3306346.3322961
Chen YHuang SYuan TZhu YQi SZhu S(2019)Holistic++ Scene Understanding: Single-View 3D Holistic Scene Parsing and Human Pose Estimation With Human-Object Interaction and Physical Commonsense2019 IEEE/CVF International Conference on Computer Vision (ICCV)10.1109/ICCV.2019.00874(8647-8656)Online publication date: Oct-2019
https://doi.org/10.1109/ICCV.2019.00874
Hu DPeng SLiu X(2018)Pixel-Level Character Motion Style Transfer using Conditional Adversarial NetworksProceedings of Computer Graphics International 201810.1145/3208159.3208161(129-138)Online publication date: 11-Jun-2018
https://dl.acm.org/doi/10.1145/3208159.3208161
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