Fetching the paper…
Reading the bibliography…
Recent advances in learning reusable motion priors have demonstrated their effectiveness in generating naturalistic behaviors.
Animation of dynamic legged locomotion. In Proceedings of the 18th annual conference on Computer graphics and interactive techniques . 349–358
Marc H Raibert and Jessica K Hodgins. 1991 · 1991
Earlier work this paper cites.
Animating human athletics. In Proceedings of the 22nd annual conference on Computer graphics and interactive techniques . 71–78
Jessica K Hodgins, Wayne L Wooten, David C Brogan, and James F O’Brien. 1995 · 1995
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 . 89–96
Victor Brian Zordan and Jessica K Hodgins. 2002 · 2002
Earlier work this paper cites.
Precomputing avatar behavior from human motion data. In Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation . 79–87
Jehee Lee and Kang Hoon Lee. 2004 · 2004
Earlier work this paper cites.
Bayesian Elo Rating
Rémi Coulom. 2005 · 2005
Earlier work this paper cites.
Pattern Recognition and Machine Learning . Vol. 4
Christopher M Bishop and Nasser M Nasrabadi. 2006 · 2006
Earlier work this paper cites.
Motion patches: building blocks for virtual environments annotated with motion data
Kang Hoon Lee, Myung Geol Choi, and Jehee Lee. 2006 · 2006
Earlier work this paper cites.
Composition of complex optimal multi-character motions. In Proceedings of the 2006 ACM SIGGRAPH/Eurographics symposium on Computer animation . 215–222
C Karen Liu, Aaron Hertzmann, and Zoran Popović. 2006 · 2006
Earlier work this paper cites.
Simulating competitive interactions using singly captured motions. In Proceedings of the 2007 ACM symposium on Virtual reality software and technology . 65–72
Hubert PH Shum, Taku Komura, and Shuntaro Yamazaki. 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.
Simbicon: Simple biped locomotion control
KangKang Yin, Kevin Loken, and Michiel Van de Panne. 2007 · 2007
Earlier work this paper cites.
Simulation of human motion data using short-horizon model-predictive control. In Computer Graphics Forum , Vol. 27. Wiley Online Library, 371–380
Marco Da Silva, Yeuhi Abe, and Jovan Popović. 2008 · 2008
Earlier work this paper cites.
Two-character motion analysis and synthesis
Taesoo Kwon, Young-Sang Cho, Sang I Park, and Sung Yong Shin. 2008 · 2008
Earlier work this paper cites.
Interaction patches for multi-character animation
Hubert PH Shum, Taku Komura, Masashi Shiraishi, and Shuntaro Yamazaki. 2008b · 2008
Earlier work this paper cites.
Simulating interactions of avatars in high dimensional state space. In Proceedings of the 2008 Symposium on interactive 3D Graphics and Games . 131–138
Hubert PH Shum, Taku Komura, and Shuntaro Yamazaki. 2008a · 2008
Earlier work this paper cites.
An analysis of model-based interval estimation for Markov decision processes
Alexander L Strehl and Michael L Littman. 2008 · 2008
Earlier work this paper cites.
Continuation methods for adapting simulated skills
KangKang Yin, Stelian Coros, Philippe Beaudoin, and Michiel Van de Panne. 2008 · 2008
Earlier work this paper cites.
Synchronized multi-character motion editing
Manmyung Kim, Kyunglyul Hyun, Jongmin Kim, and Jehee Lee. 2009 · 2009
Earlier work this paper cites.
Momentum control for balance
Adriano Macchietto, Victor Zordan, and Christian R Shelton. 2009 · 2009
Earlier work this paper cites.
Contact-aware nonlinear control of dynamic characters
Uldarico Muico, Yongjoon Lee, Jovan Popović, and Zoran Popović. 2009 · 2009
Earlier work this paper cites.
Spatial relationship preserving character motion adaptation
Edmond SL Ho, Taku Komura, and Chiew-Lan Tai. 2010 · 2010
Earlier work this paper cites.
Data-driven biped control
Yoonsang Lee, Sungeun Kim, and Jehee Lee. 2010 · 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.
Simulating multiple character interactions with collaborative and adversarial goals
Hubert PH Shum, Taku Komura, and Shuntaro Yamazaki. 2010 · 2010
Earlier work this paper cites.
Character animation in two-player adversarial games
Kevin Wampler, Erik Andersen, Evan Herbst, Yongjoon Lee, and Zoran Popović. 2010 · 2010
Earlier work this paper cites.
Modal-space control for articulated characters
Sumit Jain and C Karen Liu. 2011 · 2011
Earlier work this paper cites.
Composite control of physically simulated characters
Uldarico Muico, Jovan Popović, and Zoran Popović. 2011 · 2011
Earlier work this paper cites.
Tiling motion patches. In Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation . 117–126
Manmyung Kim, Youngseok Hwang, Kyunglyul Hyun, and Jehee Lee. 2012 · 2012
Earlier work this paper cites.
Discovery of complex behaviors through contact-invariant optimization
Igor Mordatch, Emanuel Todorov, and Zoran Popović. 2012 · 2012
Earlier work this paper cites.
Control of rotational dynamics for ground behaviors. In Proceedings of the 12th ACM SIGGRAPH/Eurographics Symposium on Computer Animation . 55–61
David F Brown, Adriano Macchietto, KangKang Yin, and Victor Zordan. 2013 · 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
Cited alongside, same era.
Auto-encoding variational bayes
Diederik P Kingma and Max Welling. 2013 · 2013
Cited alongside, same era.
Learning bicycle stunts
Jie Tan, Yuting Gu, C Karen Liu, and Greg Turk. 2014 · 2014
Cited alongside, same era.
Generating and ranking diverse multi-character interactions
Jungdam Won, Kyungho Lee, Carol O’Sullivan, Jessica K Hodgins, and Jehee Lee. 2014 · 2014
Cited alongside, same era.
Learning dexterous in-hand manipulation
OpenAI: Marcin Andrychowicz, Bowen Baker, Maciek Chociej, Rafal Jozefowicz, Bob McGrew, Jakub Pachocki, Arthur Petron, Matthias Plappert, Glenn Powell, Alex Ray, et al · 2020
Later among the works it cites.
Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2020 · 2020
Later among the works it cites.
Lei Han, Jiechao Xiong, Peng Sun, Xinghai Sun, Meng Fang, Qingwei Guo, Qiaobo Chen, Tengfei Shi, Hongsheng Yu, Xipeng Wu, and Zhengyou Zhang. 2020 · 2020
Later among the works it cites.
Moglow: Probabilistic and controllable motion synthesis using normalising flows
Gustav Eje Henter, Simon Alexanderson, and Jonas Beskow. 2020 · 2020
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.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Samuel R Bowman, Luke Vilnis, Oriol Vinyals, Andrew M Dai, Rafal Jozefowicz, and Samy Bengio. 2015 · 2015
Cited alongside, same era.
Learning reduced-order feedback policies for motion skills. In Proceedings of the 14th ACM SIGGRAPH/Eurographics Symposium on Computer Animation . 83–92
Kai Ding, Libin Liu, Michiel Van de Panne, and KangKang Yin. 2015 · 2015
Cited alongside, same era.
Andrei A Rusu, Sergio Gomez Colmenarejo, Caglar Gulcehre, Guillaume Desjardins, James Kirkpatrick, Razvan Pascanu, Volodymyr Mnih, Koray Kavukcuoglu, and Raia Hadsell. 2015 · 2015
Cited alongside, same era.
Unifying count-based exploration and intrinsic motivation
Marc Bellemare, Sriram Srinivasan, Georg Ostrovski, Tom Schaul, David Saxton, and Remi Munos. 2016 · 2016
Cited alongside, same era.
Generative adversarial imitation learning
Jonathan Ho and Stefano Ermon. 2016 · 2016
Cited alongside, same era.
Guided learning of control graphs for physics-based characters
Libin Liu, Michiel Van De Panne, and KangKang Yin. 2016 · 2016
Cited alongside, same era.
Terrain-adaptive locomotion skills using deep reinforcement learning
Xue Bin Peng, Glen Berseth, and Michiel Van de Panne. 2016 · 2016
Cited alongside, same era.
Catch & 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.
Controlvae: Controllable variational autoencoder. In International Conference on Machine Learning (ICML) . 8655–8664
Huajie Shao, Shuochao Yao, Dachun Sun, Aston Zhang, Shengzhong Liu, Dongxin Liu, Jun Wang, and Tarek Abdelzaher. 2020 · 2020
Later among the works it cites.
Tleague: A framework for competitive self-play based distributed multi-agent reinforcement learning
Peng Sun, Jiechao Xiong, Lei Han, Xinghai Sun, Shuxing Li, Jiawei Xu, Meng Fang, and Zhengyou Zhang. 2020 · 2020
Later among the works it cites.
Discretizing continuous action space for on-policy optimization. In Proceedings of the aaai conference on artificial intelligence , Vol. 34. 5981–5988
Yunhao Tang and Shipra Agrawal. 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.
Allsteps: curriculum-driven learning of stepping stone skills. In Computer Graphics Forum , Vol. 39. Wiley Online Library, 213–224
Zhaoming Xie, Hung Yu Ling, Nam Hee Kim, and Michiel van de Panne. 2020 · 2020
Later among the works it cites.
Motion recommendation for online character control
Kyungmin Cho, Chaelin Kim, Jungjin Park, Joonkyu Park, and Junyong Noh. 2021 · 2021
Later among the works it cites.
Supertrack: Motion tracking for physically simulated characters using supervised learning
Levi Fussell, Kevin Bergamin, and Daniel Holden. 2021 · 2021
Later among the works it cites.
Learning a family of motor skills from a single motion clip
Seyoung Lee, Sunmin Lee, Yongwoo Lee, and Jehee Lee. 2021 · 2021
Later among the works it cites.
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 · 2021
Later among the works it cites.
Amp: Adversarial motion priors for stylized physics-based character control
Xue Bin Peng, Ze Ma, Pieter Abbeel, Sergey Levine, and Angjoo Kanazawa. 2021 · 2021
Later among the works it cites.
Control strategies for physically simulated characters performing two-player competitive sports
Jungdam Won, Deepak Gopinath, and Jessica Hodgins. 2021 · 2021
Later among the works it cites.
Discovering diverse athletic jumping strategies
Zhiqi Yin, Zeshi Yang, Michiel Van De Panne, and KangKang Yin. 2021 · 2021
Later among the works it cites.
PADL: Language-Directed Physics-Based Character Control. In SIGGRAPH Asia 2022 Conference Papers . 1–9
Jordan Juravsky, Yunrong Guo, Sanja Fidler, and Xue Bin Peng. 2022 · 2022
Later among the works it cites.
Deep Compliant Control. In ACM SIGGRAPH 2022 Conference Proceedings . 1–9
Seunghwan Lee, Phil Sik Chang, and Jehee Lee. 2022 · 2022
Later among the works it cites.
Ganimator: Neural motion synthesis from a single sequence
Peizhuo Li, Kfir Aberman, Zihan Zhang, Rana Hanocka, and Olga Sorkine-Hornung. 2022 · 2022
Later among the works it cites.
From motor control to team play in simulated humanoid football
Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, SM Ali Eslami, Daniel Hennes, Wojciech M Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, et al · 2022
Later among the works it cites.
Ase: Large-scale reusable adversarial skill embeddings for physically simulated characters
Xue Bin Peng, Yunrong Guo, Lina Halper, Sergey Levine, and Sanja Fidler. 2022 · 2022
Later among the works it cites.
Physics-based character controllers using conditional vaes
Jungdam Won, Deepak Gopinath, and Jessica Hodgins. 2022 · 2022
Later among the works it cites.
Learning soccer juggling skills with layer-wise mixture-of-experts. In ACM SIGGRAPH 2022 Conference Proceedings . 1–9
Zhaoming Xie, Sebastian Starke, Hung Yu Ling, and Michiel van de Panne. 2022 · 2022
Later among the works it cites.
ControlVAE: Model-Based Learning of Generative Controllers for Physics-Based Characters
Heyuan Yao, Zhenhua Song, Baoquan Chen, and Libin Liu. 2022 · 2022
Later among the works it cites.
Synthesizing Physical Character-Scene Interactions
Mohamed Hassan, Yunrong Guo, Tingwu Wang, Michael Black, Sanja Fidler, and Xue Bin Peng. 2023 · 2023
Closest in time.
CALM: Conditional Adversarial Latent Models for Directable Virtual Characters. In ACM SIGGRAPH 2023 Conference Proceedings (Los Angeles, CA, USA) (SIGGRAPH ’23) . Association for Computing Machinery, New York, NY, USA
Chen Tessler, Yoni Kasten, Yunrong Guo, Shie Mannor, Gal Chechik, and Xue Bin Peng. 2023 · 2023
Closest in time.