Fetching the paper…
Reading the bibliography…
The ability to generate complex and realistic human body animations at scale, while following specific artistic constraints, has been a fundamental goal for the game and animation industry for decades.
Modeling Human Motion with Quaternion-based Neural Networks
Dario Pavllo, Christoph Feichtenhofer, Michael Auli, and David Grangier. 2019a · 1901
Earlier work this paper cites.
Least-squares fitting of two 3-D point sets
K Somani Arun, Thomas S Huang, and Steven D Blostein. 1987 · 1987
Earlier work this paper cites.
A comparison of four algorithms for estimating 3-D rigid transformations
Adele Lorusso, David W Eggert, and Robert B Fisher. 1995 · 1995
Earlier work this paper cites.
Verbs and adverbs: Multidimensional motion interpolation
Charles Rose, Michael F Cohen, and Bobby Bodenheimer. 1998 · 1998
Earlier work this paper cites.
Artist-directed inverse-kinematics using radial basis function interpolation. In Computer Graphics Forum , Vol. 20. Wiley Online Library, 239–250
Charles F Rose III, Peter-Pike J Sloan, and Michael F Cohen. 2001 · 2001
Earlier work this paper cites.
Interactive control of avatars animated with human motion data. In ACM Transactions on Graphics (ToG) , Vol. 21. ACM, 491–500
Jehee Lee, Jinxiang Chai, Paul SA Reitsma, Jessica K Hodgins, and Nancy S Pollard. 2002 · 2002
Earlier work this paper cites.
On-line locomotion generation based on motion blending. In Proceedings of the 2002 ACM SIGGRAPH/Eurographics symposium on Computer animation . ACM, 105–111
Sang Il Park, Hyun Joon Shin, and Sung Yong Shin. 2002 · 2002
Earlier work this paper cites.
Style-based inverse kinematics. In ACM transactions on graphics (TOG) , Vol. 23. ACM, 522–531
Keith Grochow, Steven L Martin, Aaron Hertzmann, and Zoran Popović. 2004 · 2004
Earlier work this paper cites.
Automated extraction and parameterization of motions in large data sets. In ACM Transactions on Graphics (ToG) , Vol. 23. ACM, 559–568
Lucas Kovar and Michael Gleicher. 2004 · 2004
Earlier work this paper cites.
ARA*: Anytime A* with provable bounds on sub-optimality. In Advances in neural information processing systems . 767–774
Maxim Likhachev, Geoffrey J Gordon, and Sebastian Thrun. 2004 · 2004
Earlier work this paper cites.
Geostatistical motion interpolation. In ACM Transactions on Graphics (TOG) , Vol. 24. ACM, 1062–1070
Tomohiko Mukai and Shigeru Kuriyama. 2005 · 2005
Earlier work this paper cites.
Constraint-based motion optimization using a statistical dynamic model
Jinxiang Chai and Jessica K. Hodgins. 2007 · 2007
Earlier work this paper cites.
Spatial keyframing for performance-driven animation. In ACM SIGGRAPH 2007 courses . ACM, 25
Takeo Igarashi, Tomer Moscovich, and John F Hughes. 2007 · 2007
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.
Gaussian Process Dynamical Models for Human Motion
Jack M. Wang, David J. Fleet, and Aaron Hertzmann. 2008 · 2007
Earlier work this paper cites.
Motion graphs. In ACM SIGGRAPH 2008 classes . ACM, 51
Lucas Kovar, Michael Gleicher, and Frédéric Pighin. 2008 · 2008
Earlier work this paper cites.
Evolved Controllers for Simulated Locomotion. In Motion in Games, Second International Workshop, MIG 2009, Zeist, The Netherlands, November 21-24, 2009. Proceedings . 219–230
Brian F. Allen and Petros Faloutsos. 2009 · 2009
Earlier work this paper cites.
Interactive generation of human animation with deformable motion models
Jianyuan Min, Yen-Lin Chen, and Jinxiang Chai. 2009 · 2009
Earlier work this paper cites.
Amazon’s Mechanical Turk: A New Source of Inexpensive, Yet High-Quality, Data?
Michael Buhrmester, Tracy Kwang, and Samuel D. Gosling. 2011 · 2011
Earlier work this paper cites.
Continuous character control with low-dimensional embeddings
Sergey Levine, Jack M. Wang, Alexis Haraux, Zoran Popovic, and Vladlen Koltun. 2012 · 2012
Cited alongside, same era.
Efficient Nonlinear Markov Models for Human Motion. In 2014 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014, Columbus, OH, USA, June 23-28, 2014 . 1314–1321
Andreas M. Lehrmann, Peter V. Gehler, and Sebastian Nowozin. 2014 · 2014
Cited alongside, same era.
Learning Complex Neural Network Policies with Trajectory Optimization. In Proceedings of the 31th International Conference on Machine Learning, ICML 2014, Beijing, China, 21-26 June 2014 . 829–837
Sergey Levine and Vladlen Koltun. 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.
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.
Deep video generation, prediction and completion of human action sequences. In Proceedings of the European Conference on Computer Vision (ECCV) . 366–382
Haoye Cai, Chunyan Bai, Yu-Wing Tai, and Chi-Keung Tang. 2018 · 2018
Later among the works it cites.
Image-to-image translation for cross-domain disentanglement. In Advances in neural information processing systems . 1287–1298
Abel Gonzalez-Garcia, Joost Van De Weijer, and Yoshua Bengio. 2018 · 2018
Later among the works it cites.
Recurrent transition networks for character locomotion. In SIGGRAPH Asia 2018 Technical Briefs . ACM, ACM Press / ACM SIGGRAPH
Félix G. Harvey and Christopher Pal. 2018 · 2018
Later among the works it cites.
Data-driven approach to simulating realistic human joint constraints. In 2018 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 1098–1103
Yifeng Jiang and C Karen Liu. 2018 · 2018
Later among the works it cites.
Learning basketball dribbling skills using trajectory optimization and deep reinforcement learning
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Pose-conditioned joint angle limits for 3D human pose reconstruction. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . 1446–1455
Ijaz Akhter and Michael J Black. 2015 · 2015
Cited alongside, same era.
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification. In Proceedings of the 2015 IEEE International Conference on Computer Vision (ICCV) (ICCV ’15) . IEEE Computer Society, Washington, DC, USA, 1026–1034
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2015 · 2015
Cited alongside, same era.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy. 2015 · 2015
Cited alongside, same era.
Interactive Control of Diverse Complex Characters with Neural Networks. In Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada . 3132–3140
Igor Mordatch, Kendall Lowrey, Galen Andrew, Zoran Popovic, and Emanuel Todorov. 2015 · 2015
Cited alongside, same era.
Task-based locomotion
Shailen Agrawal and Michiel van de Panne. 2016 · 2016
Cited alongside, same era.
A deep learning framework for character motion synthesis and editing
Daniel Holden, Jun Saito, and Taku Komura. 2016 · 2016
Cited alongside, same era.
Phase-functioned neural networks for character control
Daniel Holden, Taku Komura, and Jun Saito. 2017 · 2017
Cited alongside, same era.
Libin Liu and Jessica Hodgins. 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. 2018 · 2018
Later among the works it cites.
Neural kinematic networks for unsupervised motion retargetting. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . 8639–8648
Ruben Villegas, Jimei Yang, Duygu Ceylan, and Honglak Lee. 2018 · 2018
Later among the works it cites.
MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics. In Proceedings of the European Conference on Computer Vision (ECCV) . 265–281
Xinchen Yan, Akash Rastogi, Ruben Villegas, Kalyan Sunkavalli, Eli Shechtman, Sunil Hadap, Ersin Yumer, and Honglak Lee. 2018 · 2018
Later among the works it cites.
Learning symmetry 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.
Data-driven autocompletion for keyframe animation. In Proceedings of the 11th Annual International Conference on Motion, Interaction, and Games . 1–11
Xinyi Zhang and Michiel van de Panne. 2018 · 2018
Later among the works it cites.
CMU Graphics Lab Motion Capture Database
CMU. 2010 · 2019
Later among the works it cites.
Physics-based Full-body Soccer Motion Control for Dribbling and Shooting
Seokpyo Hong, Daesong Han, Kyungmin Cho, Joseph S. Shin, and Junyong Noh. 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.
Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling
He Wang, Edmond SL Ho, Hubert PH Shum, and Zhanxing Zhu. 2019 · 2019
Later among the works it cites.
Euler Angles — Wikipedia, The Free Encyclopedia
Wikipedia contributors. 2019 · 2019
Later among the works it cites.
Convolutional Sequence Generation for Skeleton-Based Action Synthesis
Sijie Yan, Zhizhong Li, Yuanjun Xiong, Huahan Yan, and Dahua Lin. 2019 · 2019
Later among the works it cites.
On the Continuity of Rotation Representations in Neural Networks
Yi Zhou, Connelly Barnes, Jingwan Lu, Jimei Yang, and Hao Li. 2019 · 2019
Later among the works it cites.