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Synthesizing graceful and life-like behaviors for physically simulated characters has been a fundamental challenge in computer animation.
Imitation Learning as f-Divergence Minimization
Liyiming Ke, Matt Barnes, Wen Sun, Gilwoo Lee, Sanjiban Choudhury, and Siddhartha S. Srinivasa. 2019 · 1905
Earlier work this paper cites.
Dynamic programming algorithm optimization for spoken word recognition
H. Sakoe and S. Chiba. 1978 · 1978
Earlier work this paper cites.
ALVINN: An Autonomous Land Vehicle in a Neural Network. In Proceedings of the 1st International Conference on Neural Information Processing Systems (NIPS’88) . MIT Press, Cambridge, MA, USA, 305–313
Dean A. Pomerleau. 1988 · 1988
Earlier work this paper cites.
Animation of Dynamic Legged Locomotion. In Proceedings of the 18th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH ’91) . Association for Computing Machinery, New York, NY, USA, 349–358
Marc H. Raibert and Jessica K. Hodgins. 1991 · 1991
Earlier work this paper cites.
Virtual Wind-up Toys for Animation. In Proceedings of Graphics Interface ’94 . 208–215
Michiel van de Panne, Ryan Kim, and Eugene Flume. 1994 · 1994
Earlier work this paper cites.
Practical Parameterization of Rotations Using the Exponential Map
F. Sebastin Grassia. 1998 · 1998
Earlier work this paper cites.
Introduction to Reinforcement Learning (1st ed.)
Richard S. Sutton and Andrew G. Barto. 1998 · 1998
Earlier work this paper cites.
Interactive Control of Avatars Animated with Human Motion Data
Jehee Lee, Jinxiang Chai, Paul S. A. Reitsma, Jessica K. Hodgins, and Nancy S. Pollard. 2002 · 2002
Earlier work this paper cites.
Motion Capture-Driven Simulations That Hit and React. In Proceedings of the 2002 ACM SIGGRAPH/Eurographics Symposium on Computer Animation (San Antonio, Texas) (SCA ’02) . Association for Computing Machinery, New York, NY, USA, 89–96
Victor Brian Zordan and Jessica K. Hodgins. 2002 · 2002
Earlier work this paper cites.
Apprenticeship Learning via Inverse Reinforcement Learning. In Proceedings of the Twenty-First International Conference on Machine Learning (Banff, Alberta, Canada) (ICML ’04) . Association for Computing Machinery, New York, NY, USA, 1
Pieter Abbeel and Andrew Y. Ng. 2004 · 2004
Earlier work this paper cites.
Style-Based Inverse Kinematics
Keith Grochow, Steven L. Martin, Aaron Hertzmann, and Zoran Popović. 2004 · 2004
Earlier work this paper cites.
Quantitative evaluation method for pose and motion similarity based on human perception. In 4th IEEE/RAS International Conference on Humanoid Robots, 2004. , Vol. 1. 494–512 Vol. 1
T. Harada, S. Taoka, T. Mori, and T. Sato. 2004 · 2004
Earlier work this paper cites.
Synthesis of Controllers for Stylized Planar Bipedal Walking. In Proc. of IEEE International Conference on Robotics and Animation
Dana Sharon and Michiel van de Panne. 2005 · 2005
Earlier work this paper cites.
Construction and Optimal Search of Interpolated Motion Graphs
Alla Safonova and Jessica K. Hodgins. 2007 · 2007
Earlier work this paper cites.
Simulating Biped Behaviors from Human Motion Data
Kwang Won Sok, Manmyung Kim, and Jehee Lee. 2007 · 2007
Earlier work this paper cites.
Near-Optimal Character Animation with Continuous Control. In ACM SIGGRAPH 2007 Papers (San Diego, California) (SIGGRAPH ’07) . Association for Computing Machinery, New York, NY, USA, 7–es
Adrien Treuille, Yongjoon Lee, and Zoran Popović. 2007 · 2007
Earlier work this paper cites.
Learning Omnidirectional Path Following Using Dimensionality Reduction
W. Burgard, O. Brock, and C. Stachniss. 2008 · 2008
Earlier work this paper cites.
Simulation of Human Motion Data using Short-Horizon Model-Predictive Control
M. Da Silva, Y. Abe, and J. Popovic. 2008 · 2008
Earlier work this paper cites.
Emulating human perception of motion similarity
Jeff Tang, Howard Leung, Taku Komura, and Hubert Shum. 2008 · 2008
Earlier work this paper cites.
Maximum Entropy Inverse Reinforcement Learning. In Proceedings of the 23rd National Conference on Artificial Intelligence - Volume 3 (Chicago, Illinois) (AAAI’08) . AAAI Press, 1433–1438
Brian D. Ziebart, Andrew Maas, J. Andrew Bagnell, and Anind K. Dey. 2008 · 2008
Earlier work this paper cites.
Contact-Aware Nonlinear Control of Dynamic Characters. In ACM SIGGRAPH 2009 Papers (New Orleans, Louisiana) (SIGGRAPH ’09) . Association for Computing Machinery, New York, NY, USA, Article 81, 9 pages
Uldarico Muico, Yongjoon Lee, Jovan Popović, and Zoran Popović. 2009 · 2009
Earlier work this paper cites.
Optimizing Walking Controllers. In ACM SIGGRAPH Asia 2009 Papers (Yokohama, Japan) (SIGGRAPH Asia ’09) . Association for Computing Machinery, New York, NY, USA, Article 168, 8 pages
Jack M. Wang, David J. Fleet, and Aaron Hertzmann. 2009 · 2009
Earlier work this paper cites.
Synthesis of Responsive Motion Using a Dynamic Model
Yuting Ye and C. Karen Liu. 2010 · 2009
Earlier work this paper cites.
Data-Driven Biped Control
Yoonsang Lee, Sungeun Kim, and Jehee Lee. 2010a · 2010
Earlier work this paper cites.
Motion Fields for Interactive Character Locomotion
Yongjoon Lee, Kevin Wampler, Gilbert Bernstein, Jovan Popović, and Zoran Popović. 2010b · 2010
Earlier work this paper cites.
Sampling-based contact-rich motion control
Libin Liu, KangKang Yin, Michiel van de Panne, Tianjia Shao, and Weiwei Xu. 2010 · 2010
Earlier work this paper cites.
Rectified Linear Units Improve Restricted Boltzmann Machines. In Proceedings of the 27th International Conference on International Conference on Machine Learning (Haifa, Israel) (ICML’10) . Omnipress, Madison, WI, USA, 807–814
Vinod Nair and Geoffrey E. Hinton. 2010 · 2010
Earlier work this paper cites.
Space-Time Planning with Parameterized Locomotion Controllers
Sergey Levine, Yongjoon Lee, Vladlen Koltun, and Zoran Popović. 2011 · 2011
Earlier work this paper cites.
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning (Proceedings of Machine Learning Research, Vol. 15) , Geoffrey Gordon, David Dunson, and Miroslav Dudík (Eds.). JMLR Workshop and Conference Proceedings, Fort Lauderdale, FL, USA, 627–635
Stephane Ross, Geoffrey Gordon, and Drew Bagnell. 2011 · 2011
Earlier work this paper cites.
Trajectory Optimization for Full-Body Movements with Complex Contacts
M. Al Borno, M. de Lasa, and A. Hertzmann. 2013 · 2012
Earlier work this paper cites.
Continuous Character Control with Low-Dimensional Embeddings
Sergey Levine, Jack M. Wang, Alexis Haraux, Zoran Popović, and Vladlen Koltun. 2012 · 2012
Cited alongside, same era.
Terrain runner: control, parameterization, composition, and planning for highly dynamic motions
Libin Liu, KangKang Yin, Michiel van de Panne, and Baining Guo. 2012 · 2012
Cited alongside, same era.
Discovery of Complex Behaviors through Contact-Invariant Optimization
Igor Mordatch, Emanuel Todorov, and Zoran Popović. 2012 · 2012
Cited alongside, same era.
Optimizing Locomotion Controllers Using Biologically-Based Actuators and Objectives
Jack M. Wang, Samuel R. Hamner, Scott L. Delp, and Vladlen Koltun. 2012 · 2012
Cited alongside, same era.
Bullet physics library
Erwin Coumans et al · 2013
Cited alongside, same era.
Flexible Muscle-Based Locomotion for Bipedal Creatures
Thomas Geijtenbeek, Michiel van de Panne, and A. Frank van der Stappen. 2013 · 2013
Momentum-Mapped Inverted Pendulum Models for Controlling Dynamic Human Motions
Taesoo Kwon and Jessica K. Hodgins. 2017 · 2017
Later among the works it cites.
Least Squares Generative Adversarial Networks. In 2017 IEEE International Conference on Computer Vision (ICCV) . 2813–2821
X. Mao, Q. Li, H. Xie, R. Y. K. Lau, Z. Wang, and S. P. Smolley. 2017 · 2017
Later among the works it cites.
Learning human behaviors from motion capture by adversarial imitation
Josh Merel, Yuval Tassa, Dhruva TB, Sriram Srinivasan, Jay Lemmon, Ziyu Wang, Greg Wayne, and Nicolas Heess. 2017 · 2017
Later among the works it cites.
DeepLoco: Dynamic Locomotion Skills Using Hierarchical Deep Reinforcement Learning
Xue Bin Peng, Glen Berseth, Kangkang Yin, and Michiel Van De Panne. 2017 · 2017
Later among the works it cites.
Proximal Policy Optimization Algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017 · 2017
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Cited alongside, same era.
Animating Human Lower Limbs Using Contact-Invariant Optimization
Igor Mordatch, Jack M. Wang, Emanuel Todorov, and Vladlen Koltun. 2013 · 2013
Cited alongside, same era.
Generative Adversarial Nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014 · 2014
Cited alongside, same era.
Diederik P. Kingma and Max Welling. 2014 · 2014
Cited alongside, same era.
Learning Bicycle Stunts
Jie Tan, Yuting Gu, C. Karen Liu, and Greg Turk. 2014 · 2014
Cited alongside, same era.
Generalizing Locomotion Style to New Animals with Inverse Optimal Regression
Kevin Wampler, Zoran Popović, and Jovan Popović. 2014 · 2014
Cited alongside, same era.
TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng. 2015 · 2015
Cited alongside, same era.
Later among the works it cites.
Robust Imitation of Diverse Behaviors. In Advances in Neural Information Processing Systems , I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett (Eds.), Vol. 30. Curran Associates, Inc., 5320–5329
Ziyu Wang, Josh S Merel, Scott E Reed, Nando de Freitas, Gregory Wayne, and Nicolas Heess. 2017 · 2017
Later among the works it cites.
Physics-Based Motion Capture Imitation with Deep Reinforcement Learning. In Proceedings of the 11th Annual International Conference on Motion, Interaction, and Games (Limassol, Cyprus) (MIG ’18) . Association for Computing Machinery, New York, NY, USA, Article 1, 10 pages
Nuttapong Chentanez, Matthias Müller, Miles Macklin, Viktor Makoviychuk, and Stefan Jeschke. 2018 · 2018
Later among the works it cites.
Latent Space Policies for Hierarchical Reinforcement Learning (Proceedings of Machine Learning Research, Vol. 80) , Jennifer Dy and Andreas Krause (Eds.). PMLR, Stockholmsmässan, Stockholm Sweden, 1851–1860
Tuomas Haarnoja, Kristian Hartikainen, Pieter Abbeel, and Sergey Levine. 2018 · 2018
Later among the works it cites.
Learning an Embedding Space for Transferable Robot Skills. In International Conference on Learning Representations
Karol Hausman, Jost Tobias Springenberg, Ziyu Wang, Nicolas Heess, and Martin Riedmiller. 2018 · 2018
Later among the works it cites.
End-to-end Recovery of Human Shape and Pose. In Computer Vision and Pattern Regognition (CVPR)
Angjoo Kanazawa, Michael J. Black, David W. Jacobs, and Jitendra Malik. 2018 · 2018
Later among the works it cites.
Interactive Character Animation by Learning Multi-Objective Control
Kyungho Lee, Seyoung Lee, and Jehee Lee. 2018 · 2018
Later among the works it cites.
Which Training Methods for GANs do actually Converge?. In Proceedings of the 35th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 80) , Jennifer Dy and Andreas Krause (Eds.). PMLR, Stockholmsmässan, Stockholm Sweden, 3481–3490
Lars Mescheder, Andreas Geiger, and Sebastian Nowozin. 2018 · 2018
Later among the works it cites.
DeepMimic: Example-guided Deep Reinforcement Learning of Physics-based Character Skills
Xue Bin Peng, Pieter Abbeel, Sergey Levine, and Michiel van de Panne. 2018a · 2018
Later among the works it cites.
SFV: Reinforcement Learning of Physical Skills from Videos
Xue Bin Peng, Angjoo Kanazawa, Jitendra Malik, Pieter Abbeel, and Sergey Levine. 2018b · 2018
Later among the works it cites.
Yuval Tassa, Yotam Doron, Alistair Muldal, Tom Erez, Yazhe Li, Diego de Las Casas, David Budden, Abbas Abdolmaleki, Josh Merel, Andrew Lefrancq, Timothy P. Lillicrap, and Martin A. Riedmiller. 2018 · 2018
Later among the works it cites.
Generative Adversarial Imitation from Observation
Faraz Torabi, Garrett Warnell, and Peter Stone. 2018 · 2018
Later among the works it cites.
Learning Symmetric and Low-Energy Locomotion
Wenhao Yu, Greg Turk, and C. Karen Liu. 2018 · 2018
Later among the works it cites.
Mode-Adaptive Neural Networks for Quadruped Motion Control
He Zhang, Sebastian Starke, Taku Komura, and Jun Saito. 2018 · 2018
Later among the works it cites.
DReCon: Data-Driven Responsive Control of Physics-Based Characters
Kevin Bergamin, Simon Clavet, Daniel Holden, and James Richard Forbes. 2019 · 2019
Later among the works it cites.
Synthesis of Biologically Realistic Human Motion Using Joint Torque Actuation
Yifeng Jiang, Tom Van Wouwe, Friedl De Groote, and C. Karen Liu. 2019 · 2019
Later among the works it cites.
Scalable Muscle-Actuated Human Simulation and Control
Seunghwan Lee, Moonseok Park, Kyoungmin Lee, and Jehee Lee. 2019 · 2019
Later among the works it cites.
Neural Probabilistic Motor Primitives for Humanoid Control. In International Conference on Learning Representations
Josh Merel, Leonard Hasenclever, Alexandre Galashov, Arun Ahuja, Vu Pham, Greg Wayne, Yee Whye Teh, and Nicolas Heess. 2019 · 2019
Later among the works it cites.
Learning Predict-and-Simulate Policies from Unorganized Human Motion Data
Soohwan Park, Hoseok Ryu, Seyoung Lee, Sunmin Lee, and Jehee Lee. 2019 · 2019
Later among the works it cites.
Neural State Machine for Character-Scene Interactions
Sebastian Starke, He Zhang, Taku Komura, and Jun Saito. 2019 · 2019
Later among the works it cites.
Character Controllers Using Motion VAEs
Hung Yu Ling, Fabio Zinno, George Cheng, and Michiel van de Panne. 2020 · 2020
Later among the works it cites.
CARL: Controllable Agent with Reinforcement Learning for Quadruped Locomotion
Ying-Sheng Luo, Jonathan Hans Soeseno, Trista Pei-Chun Chen, and Wei-Chao Chen. 2020 · 2020
Later among the works it cites.
Learning Latent Plans from Play. In Proceedings of the Conference on Robot Learning (Proceedings of Machine Learning Research, Vol. 100) , Leslie Pack Kaelbling, Danica Kragic, and Komei Sugiura (Eds.). PMLR, 1113–1132
Corey Lynch, Mohi Khansari, Ted Xiao, Vikash Kumar, Jonathan Tompson, Sergey Levine, and Pierre Sermanet. 2020 · 2020
Later among the works it cites.
Catch and Carry: Reusable Neural Controllers for Vision-Guided Whole-Body Tasks
Josh Merel, Saran Tunyasuvunakool, Arun Ahuja, Yuval Tassa, Leonard Hasenclever, Vu Pham, Tom Erez, Greg Wayne, and Nicolas Heess. 2020 · 2020
Later among the works it cites.
A Scalable Approach to Control Diverse Behaviors for Physically Simulated Characters
Jungdam Won, Deepak Gopinath, and Jessica Hodgins. 2020 · 2020
Later among the works it cites.