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We present SMPLOlympics, a collection of physically simulated environments that allow humanoids to compete in a variety of Olympic sports.
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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Keep it smpl: Automatic estimation of 3d human pose and shape from a single image
Federica Bogo, Angjoo Kanazawa, Christoph Lassner, Peter Gehler, Javier Romero, and Michael J Black · 2016
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Openai gym, 2016
Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
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Proximal policy optimization algorithms, 2017
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Latent space policies for hierarchical reinforcement learning
Tuomas Haarnoja, Kristian Hartikainen, Pieter Abbeel, and Sergey Levine · 2018
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Learning basketball dribbling skills using trajectory optimization and deep reinforcement learning
Libin Liu and Jessica Hodgins · 2018
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Neural probabilistic motor primitives for humanoid control, 2018
Josh Merel, Leonard Hasenclever, Alexandre Galashov, Arun Ahuja, Vu Pham, Greg Wayne, Yee Whye Teh, and Nicolas Heess · 2018
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Deepmimic
Xue Bin Peng, Pieter Abbeel, Sergey Levine, and Michiel van de Panne · 2018
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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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Expressive body capture: 3d hands, face, and body from a single image
Georgios Pavlakos, Vasileios Choutas, Nima Ghorbani, Timo Bolkart, Ahmed A. A. Osman, Dimitrios Tzionas, and Michael J. Black · 2019
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On the continuity of rotation representations in neural networks
Yi Zhou, Connelly Barnes, Jingwan Lu, Jimei Yang, and Hao Li · 2019
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CoMic: Complementary task learning & mimicry for reusable skills
Leonard Hasenclever, Fabio Pardo, Raia Hadsell, Nicolas Heess, and Josh Merel · 2020
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dm_control: Software and tasks for continuous control
Saran Tunyasuvunakool, Alistair Muldal, Yotam Doron, Siqi Liu, Steven Bohez, Josh Merel, Tom Erez, Timothy Lillicrap, Nicolas Heess, and Yuval Tassa · 2020
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From motor control to team play in simulated humanoid football
Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S M Ali Eslami, Daniel Hennes, Wojciech M Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D Tracey, Karl Tuyls, Thore Graepel, and Nicolas Heess · 2021
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Isaac gym: High performance gpu-based physics simulation for robot learning
Viktor Makoviychuk, Lukasz Wawrzyniak, Yunrong Guo, Michelle Lu, Kier Storey, Miles Macklin, David Hoeller, Nikita Rudin, Arthur Allshire, Ankur Handa, and Gavriel State · 2021
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Amp: Adversarial motion priors for stylized physics-based character control
Xue Bin Peng, Ze Ma, Pieter Abbeel, Sergey Levine, and Angjoo Kanazawa · 2021
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Pmp: Learning to physically interact with environments using part-wise motion priors
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C· ase: Learning conditional adversarial skill embeddings for physics-based characters
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Eureka: Human-level reward design via coding large language models
Yecheng Jason Ma, William Liang, Guanzhi Wang, De-An Huang, Osbert Bastani, Dinesh Jayaraman, Yuke Zhu, Linxi Fan, and Anima Anandkumar · 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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Physhoi: Physics-based imitation of dynamic human-object interaction
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Control strategies for physically simulated characters performing two-player competitive sports
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Discovering diverse athletic jumping strategies
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Universal humanoid motion representations for physics-based control
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Yinhuai Wang, Jing Lin, Ailing Zeng, Zhengyi Luo, Jian Zhang, and Lei Zhang · 2023
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Composite motion learning with task control
Pei Xu, Xiumin Shang, Victor Zordan, and Ioannis Karamouzas · 2023
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Decoupling human and camera motion from videos in the wild
Vickie Ye, Georgios Pavlakos, Jitendra Malik, and Angjoo Kanazawa · 2023
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Learning physically simulated tennis skills from broadcast videos
Haotian Zhang, Ye Yuan, Viktor Makoviychuk, Yunrong Guo, Sanja Fidler, Xue Bin Peng, and Kayvon Fatahalian · 2023
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Neural categorical priors for physics-based character control
Qingxu Zhu, He Zhang, Mengting Lan, and Lei Han · 2023
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Humanoidbench: Simulated humanoid benchmark for whole-body locomotion and manipulation
Carmelo Sferrazza, Dun-Ming Huang, Xingyu Lin, Youngwoon Lee, and Pieter Abbeel · 2024
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Strategy and skill learning for physics-based table tennis animation
Jiashun Wang, Jessica Hodgins, and Jungdam Won · 2024
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