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Human motion is highly diverse and dynamic, posing challenges for imitation learning algorithms that aim to generalize motor skills for controlling simulated characters.
Composable controllers for physics-based character animation
Petros Faloutsos, Michiel Van de Panne, and Demetri Terzopoulos · 2001
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Hiroaki Kitano · 2002
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Modularity: understanding the development and evolution of natural complex systems
Werner Callebaut and Diego Rasskin-Gutman · 2005
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Learning physics-based motion style with nonlinear inverse optimization
C Karen Liu, Aaron Hertzmann, and Zoran Popović · 2005
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Arend Hintze and Christoph Adami · 2008
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Sampling-based contact-rich motion control
Libin Liu, KangKang Yin, Michiel Van de Panne, Tianjia Shao, and Weiwei Xu · 2010
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Physically Plausible Simulation for Character Animation
Sergey Levine and Jovan Popovic · 2012
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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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Learning to schedule control fragments for physics-based characters using deep q-learning
Libin Liu and Jessica Hodgins · 2017
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Deeploco: dynamic locomotion skills using hierarchical deep reinforcement learning
Xue Bin Peng, Glen Berseth, Kangkang Yin, and Michiel Van De Panne · 2017
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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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Libin Liu and Jessica Hodgins · 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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Neural probabilistic motor primitives for humanoid control
Josh Merel, Leonard Hasenclever, Alexandre Galashov, Arun Ahuja, Vu Pham, Greg Wayne, Yee Whye Teh, and Nicolas Heess · 2019
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MCP: learning composable hierarchical control with multiplicative compositional policies
Xue Bin Peng, Michael Chang, Grace Zhang, Pieter Abbeel, and Sergey Levine · 2019
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Character controllers using motion vaes
Hung Yu Ling, Fabio Zinno, George Cheng, and Michiel van de Panne · 2020
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A scalable approach to control diverse behaviors for physically simulated characters
Jungdam Won, Deepak Gopinath, and Jessica Hodgins · 2020
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Residual force control for agile human behavior imitation and extended motion synthesis
Ye Yuan and Kris Kitani · 2020
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Dynamics-regulated kinematic policy for egocentric pose estimation
Zhengyi Luo, Ryo Hachiuma, Ye Yuan, and Kris Kitani · 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, N. 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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Control strategies for physically simulated characters performing two-player competitive sports
Jungdam Won, Deepak Gopinath, and Jessica Hodgins · 2021
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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
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Perpetual humanoid control for real-time simulated avatars
Zhengyi Luo, Jinkun Cao, Alexander W. Winkler, Kris Kitani, and Weipeng Xu · 2023
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Insactor: Instruction-driven physics-based characters
Jiawei Ren, Mingyuan Zhang, Cunjun Yu, Xiao Ma, Liang Pan, and Ziwei Liu · 2023
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Calm: Conditional adversarial latent models for directable virtual characters
Chen Tessler, Yoni Kasten, Yunrong Guo, Shie Mannor, Gal Chechik, and Xue Bin Peng · 2023
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Human motion diffusion model
Guy Tevet, Sigal Raab, Brian Gordon, Yoni Shafir, Daniel Cohen-or, and Amit Haim Bermano · 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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Physdiff: Physics-guided human motion diffusion model
Ye Yuan, Jiaming Song, Umar Iqbal, Arash Vahdat, and Jan Kautz · 2023
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Motion puzzle: Arbitrary motion style transfer by body part
Deok-Kyeong Jang, Soomin Park, and Sung-Hee Lee · 2022
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Padl: Language-directed physics-based character control
Jordan Juravsky, Yunrong Guo, Sanja Fidler, and Xue Bin Peng · 2022
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Learning virtual chimeras by dynamic motion reassembly
Seyoung Lee, Jiye Lee, and Jehee Lee · 2022
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Ase: Large-scale reusable adversarial skill embeddings for physically simulated characters
Xue Bin Peng, Yunrong Guo, Lina Halper, Sergey Levine, and Sanja Fidler · 2022
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Complexity of modular neuromuscular control increases and variability decreases during human locomotor development
Francesca Sylos-Labini, Valentina La Scaleia, Germana Cappellini, Arthur Dewolf, Adele Fabiano, Irina A Solopova, Vito Mondì, Yury Ivanenko, and Francesco Lacquaniti · 2022
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MoCapAct: A multi-task dataset for simulated humanoid control
Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri, Ricky Loynd, Ching-An Cheng, and Matthew Hausknecht · 2022
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Questsim: Human motion tracking from sparse sensors with simulated avatars
Alexander Winkler, Jungdam Won, and Yuting Ye · 2022
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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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Anyskill: Learning open-vocabulary physical skill for interactive agents
Jieming Cui, Tengyu Liu, Nian Liu, Yaodong Yang, Yixin Zhu, and Siyuan Huang · 2024
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Self-correcting self-consuming loops for generative model training
Nate Gillman, Michael Freeman, Daksh Aggarwal, Chia-Hong Hsu, Calvin Luo, Yonglong Tian, and Chen Sun · 2024
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Como: Controllable motion generation through language guided pose code editing
Yiming Huang, Weilin Wan, Yue Yang, Chris Callison-Burch, Mark Yatskar, and Lingjie Liu · 2024
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Motiongpt: Human motion as a foreign language
Biao Jiang, Xin Chen, Wen Liu, Jingyi Yu, Gang Yu, and Tao Chen · 2024
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Superpadl: Scaling language-directed physics-based control with progressive supervised distillation
Jordan Juravsky, Yunrong Guo, Sanja Fidler, and Xue Bin Peng · 2024
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Maskedmimic: Unified physics-based character control through masked motion
Chen Tessler, Yunrong Guo, Ofir Nabati, Gal Chechik, and Xue Bin Peng · 2024
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Closd: Closing the loop between simulation and diffusion for multi-task character control, 2024
Guy Tevet, Sigal Raab, Setareh Cohan, Daniele Reda, Zhengyi Luo, Xue Bin Peng, Amit H. Bermano, and Michiel van de Panne · 2024
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Tlcontrol: Trajectory and language control for human motion synthesis
Weilin Wan, Zhiyang Dou, Taku Komura, Wenping Wang, Dinesh Jayaraman, and Lingjie Liu · 2024
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Template free reconstruction of human-object interaction with procedural interaction generation
Xianghui Xie, Bharat Lal Bhatnagar, Jan Eric Lenssen, and Gerard Pons-Moll · 2024
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Emdm: Efficient motion diffusion model for fast and high-quality motion generation
Wenyang Zhou, Zhiyang Dou, Zeyu Cao, Zhouyingcheng Liao, Jingbo Wang, Wenjia Wang, Yuan Liu, Taku Komura, Wenping Wang, and Lingjie Liu · 2024
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