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Interactive motion synthesis is essential in creating immersive experiences in entertainment applications, such as video games and virtual reality.
Verbs and adverbs: Multidimensional motion interpolation
Charles Rose, Michael F Cohen, and Bobby Bodenheimer · 1998
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Bayesian reconstruction of 3d human motion from single-camera video
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Interactive motion generation from examples
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Interactive control of avatars animated with human motion data
Jehee Lee, Jinxiang Chai, Paul SA Reitsma, Jessica K Hodgins, and Nancy S Pollard · 2002
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On-line locomotion generation based on motion blending
Sang Il Park, Hyun Joon Shin, and Sung Yong Shin · 2002
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Style-based inverse kinematics
Keith Grochow, Steven L Martin, Aaron Hertzmann, and Zoran Popović · 2004
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Synthesizing physically realistic human motion in low-dimensional, behavior-specific spaces
Alla Safonova, Jessica K Hodgins, and Nancy S Pollard · 2004
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Jinxiang Chai and Jessica K Hodgins · 2005
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Geostatistical motion interpolation
Tomohiko Mukai and Shigeru Kuriyama · 2005
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Construction and optimal search of interpolated motion graphs
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Gaussian process dynamical models for human motion
Jack M Wang, David J Fleet, and Aaron Hertzmann · 2007
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Motion graphs
Lucas Kovar, Michael Gleicher, and Frédéric Pighin · 2008
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Motion rings for interactive gait synthesis
Tomohiko Mukai · 2011
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Continuous character control with low-dimensional embeddings
Sergey Levine, Jack M Wang, Alexis Haraux, Zoran Popović, and Vladlen Koltun · 2012
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Motion graphs++ a compact generative model for semantic motion analysis and synthesis
Jianyuan Min and Jinxiang Chai · 2012
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Recurrent network models for kinematic tracking
Katerina Fragkiadaki, Sergey Levine, and Jitendra Malik · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Motion grammars for character animation
Kyunglyul Hyun, Kyungho Lee, and Jehee Lee · 2016
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Phase-functioned neural networks for character control
Daniel Holden, Taku Komura, and Jun Saito · 2017
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Recurrent transition networks for character locomotion
Félix G Harvey and Christopher Pal · 2018
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Character control with neural networks and machine learning
Daniel Holden · 2018
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Learned motion matching
Marko Kolsi, Mikko Mononen, and Joonas Javanainen · 2018
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Quaternet: A quaternion-based recurrent model for human motion
Dario Pavllo, David Grangier, and Michael Auli · 2018
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Mode-adaptive neural networks for quadruped motion control
He Zhang, Sebastian Starke, Taku Komura, and Jun Saito · 2018
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On the variance of the adaptive learning rate and beyond
Liyuan Liu, Haoming Jiang, Pengcheng He, Weizhu Chen, Xiaodong Liu, Jianfeng Gao, and Jiawei Han · 2019
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Is conditional generative modeling all you need for decision-making?
Anurag Ajay, Yilun Du, Abhi Gupta, Joshua Tenenbaum, Tommi Jaakkola, and Pulkit Agrawal · 2022
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Listen, denoise, action! audio-driven motion synthesis with diffusion models
Simon Alexanderson, Rajmund Nagy, Jonas Beskow, and Gustav Eje Henter · 2022
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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2022
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Imagen video: High definition video generation with diffusion models
Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang, Ruiqi Gao, Alexey Gritsenko, Diederik P Kingma, Ben Poole, Mohammad Norouzi, David J Fleet, et al · 2022
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Soohwan Park, Hoseok Ryu, Seyoung Lee, Sunmin Lee, and Jehee Lee · 2019
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Combining recurrent neural networks and adversarial training for human motion synthesis and control
Zhiyong Wang, Jinxiang Chai, and Shihong Xia · 2019
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Learning energy-based models by diffusion recovery likelihood
Ruiqi Gao, Yang Song, Ben Poole, Ying Nian Wu, and Diederik P Kingma · 2020
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Robust motion in-betweening
Félix G. Harvey, Mike Yurick, Derek Nowrouzezahrai, and Christopher Pal · 2020
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Moglow: Probabilistic and controllable motion synthesis using normalising flows
Gustav Eje Henter, Simon Alexanderson, and Jonas Beskow · 2020
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Denoising diffusion probabilistic models
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Character controllers using motion vaes
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Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, and Andrea Dittadi · 2022
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Planning with diffusion for flexible behavior synthesis
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Pretrained diffusion models for unified human motion synthesis
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Hierarchical text-conditional image generation with clip latents
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Deepphase: Periodic autoencoders for learning motion phase manifolds
Sebastian Starke, Ian Mason, and Taku Komura · 2022
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Guy Tevet, Sigal Raab, Brian Gordon, Yonatan Shafir, Daniel Cohen-Or, and Amit H Bermano · 2022
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Mcvd-masked conditional video diffusion for prediction, generation, and interpolation
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Physdiff: Physics-guided human motion diffusion model
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Motiondiffuse: Text-driven human motion generation with diffusion model
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https://www.ubisoft.com/en-us/game/for-honor
For honor · 2023
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Motion in-betweening with phase manifolds
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