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We address the problem of generating realistic 3D motions of humans interacting with objects in a scene.
SMPL: A skinned multi-person linear model
Matthew Loper, Naureen Mahmood, Javier Romero, Gerard Pons-Moll, and Michael J. Black · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Pigraphs: learning interaction snapshots from observations
Manolis Savva, Angel X Chang, Pat Hanrahan, Matthew Fisher, and Matthias Nießner · 2016
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Phase-functioned neural networks for character control
Daniel Holden, Taku Komura, and Jun Saito · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Resolving 3d human pose ambiguities with 3d scene constraints
Mohamed Hassan, Vasileios Choutas, Dimitrios Tzionas, and Michael J Black · 2019
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Amass: Archive of motion capture as surface shapes
Naureen Mahmood, Nima Ghorbani, Nikolaus F Troje, Gerard Pons-Moll, and Michael J Black · 2019
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Pyrender
Matthew Matl · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
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Super-convergence: Very fast training of neural networks using large learning rates
Leslie N Smith and Nicholay Topin · 2019
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Neural state machine for character-scene interactions
Sebastian Starke, He Zhang, Taku Komura, and Jun Saito · 2019
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Context-aware human motion prediction
Enric Corona, Albert Pumarola, Guillem Alenya, and Francesc Moreno-Noguer · 2020
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Moglow: Probabilistic and controllable motion synthesis using normalising flows
Gustav Eje Henter, Simon Alexanderson, and Jonas Beskow · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Grasping field: Learning implicit representations for human grasps
Korrawe Karunratanakul, Jinlong Yang, Yan Zhang, Michael J Black, Krikamol Muandet, and Siyu Tang · 2020
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Grab: A dataset of whole-body human grasping of objects
Omid Taheri, Nima Ghorbani, Michael J Black, and Dimitrios Tzionas · 2020
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Fourier features let networks learn high frequency functions in low dimensional domains
Matthew Tancik, Pratul Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan Barron, and Ren Ng · 2020
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Learning to sit: Synthesizing human-chair interactions via hierarchical control
Yu-Wei Chao, Jimei Yang, Weifeng Chen, and Jia Deng · 2021
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Dc3: A learning method for optimization with hard constraints
Priya L Donti, David Rolnick, and J Zico Kolter · 2021
Cited alongside, same era.
Human poseitioning system (hps): 3d human pose estimation and self-localization in large scenes from body-mounted sensors
Vladimir Guzov, Aymen Mir, Torsten Sattler, and Gerard Pons-Moll · 2021
Cited alongside, same era.
Stochastic scene-aware motion prediction
Mohamed Hassan, Duygu Ceylan, Ruben Villegas, Jun Saito, Jimei Yang, Yi Zhou, and Michael J Black · 2021
Cited alongside, same era.
Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
Cited alongside, same era.
Action-conditioned 3d human motion synthesis with transformer vae
Mathis Petrovich, Michael J Black, and Gül Varol · 2021
Cited alongside, same era.
Julen Urain, Niklas Funk, Georgia Chalvatzaki, and Jan Peters · 2022
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Towards diverse and natural scene-aware 3d human motion synthesis
Jingbo Wang, Yu Rong, Jingyuan Liu, Sijie Yan, Dahua Lin, and Bo Dai · 2022
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Humanise: Language-conditioned human motion generation in 3d scenes
Zan Wang, Yixin Chen, Tengyu Liu, Yixin Zhu, Wei Liang, and Siyuan Huang · 2022
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Neural fields in visual computing and beyond
Yiheng Xie, Towaki Takikawa, Shunsuke Saito, Or Litany, Shiqin Yan, Numair Khan, Federico Tombari, James Tompkin, Vincent Sitzmann, and Srinath Sridhar · 2022
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Scene synthesis from human motion
Sifan Ye, Yixing Wang, Jiaman Li, Dennis Park, C Karen Liu, Huazhe Xu, and Jiajun Wu · 2022
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Abhinanda R Punnakkal, Arjun Chandrasekaran, Nikos Athanasiou, Alejandra Quiros-Ramirez, and Michael J Black · 2021
Cited alongside, same era.
Humor: 3d human motion model for robust pose estimation
Davis Rempe, Tolga Birdal, Aaron Hertzmann, Jimei Yang, Srinath Sridhar, and Leonidas J. Guibas · 2021
Cited alongside, same era.
Synthesizing long-term 3d human motion and interaction in 3d scenes
Jiashun Wang, Huazhe Xu, Jingwei Xu, Sifei Liu, and Xiaolong Wang · 2021
Cited alongside, same era.
Scene-aware generative network for human motion synthesis
Jingbo Wang, Sijie Yan, Bo Dai, and Dahua Lin · 2021
Cited alongside, same era.
Behave: Dataset and method for tracking human object interactions
Bharat Lal Bhatnagar, Xianghui Xie, Ilya Petrov, Cristian Sminchisescu, Christian Theobalt, and Gerard Pons-Moll · 2022
Cited alongside, same era.
Generating diverse and natural 3d human motions from text
Chuan Guo, Shihao Zou, Xinxin Zuo, Sen Wang, Wei Ji, Xingyu Li, and Li Cheng · 2022
Cited alongside, same era.
Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2022
Cited alongside, same era.
Mingyuan Zhang, Zhongang Cai, Liang Pan, Fangzhou Hong, Xinying Guo, Lei Yang, and Ziwei Liu · 2022
Later among the works it cites.
Couch: Towards controllable human-chair interactions
Xiaohan Zhang, Bharat Lal Bhatnagar, Sebastian Starke, Vladimir Guzov, and Gerard Pons-Moll · 2022
Later among the works it cites.
The wanderings of odysseus in 3d scenes
Yan Zhang and Siyu Tang · 2022
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Gimo: Gaze-informed human motion prediction in context
Yang Zheng, Yanchao Yang, Kaichun Mo, Jiaman Li, Tao Yu, Yebin Liu, C Karen Liu, and Leonidas J Guibas · 2022
Later among the works it cites.
https://thehive.ai/
Hive.ai · 2023
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Police: Provably optimal linear constraint enforcement for deep neural networks
Randall Balestriero and Yann LeCun · 2023
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Mofusion: A framework for denoising-diffusion-based motion synthesis
Rishabh Dabral, Muhammad Hamza Mughal, Vladislav Golyanik, and Christian Theobalt · 2023
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Imos: Intent-driven full-body motion synthesis for human-object interactions
Anindita Ghosh, Rishabh Dabral, Vladislav Golyanik, Christian Theobalt, and Philipp Slusallek · 2023
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Diffusion-based generation, optimization, and planning in 3d scenes
Siyuan Huang, Zan Wang, Puhao Li, Baoxiong Jia, Tengyu Liu, Yixin Zhu, Wei Liang, and Song-Chun Zhu · 2023
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Generating continual human motion in diverse 3d scenes
Aymen Mir, Xavier Puig, Angjoo Kanazawa, and Gerard Pons-Moll · 2023
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Trace and pace: Controllable pedestrian animation via guided trajectory diffusion
Davis Rempe, Zhengyi Luo, Xue Bin Peng, Ye Yuan, Kris Kitani, Karsten Kreis, Sanja Fidler, and Or Litany · 2023
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Human motion diffusion model
Guy Tevet, Sigal Raab, Brian Gordon, Yonatan Shafir, Amit H Bermano, and Daniel Cohen-Or · 2023
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Neural grasp distance fields for robot manipulation
Thomas Weng, David Held, Franziska Meier, and Mustafa Mukadam · 2023
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MIME: Human-aware 3D scene generation
Hongwei Yi, Chun-Hao P. Huang, Shashank Tripathi, Lea Hering, Justus Thies, and Michael J. Black · 2023
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