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We tackle the problem of action-conditioned generation of realistic and diverse human motion sequences.
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Dariu M. Gavrila · 1999
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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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Human3.6M: Large scale datasets and predictive methods for 3D human sensing in natural environments
Catalin Ionescu, Dragos Papava, Vlad Olaru, and Cristian Sminchisescu · 2014
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2014
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Recurrent network models for human dynamics
Katerina Fragkiadaki, Sergey Levine, Panna Felsen, and Jitendra Malik · 2015
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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 structured output representation using deep conditional generative models
Kihyuk Sohn, Honglak Lee, and Xinchen Yan · 2015
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Gaussian error linear units (GELUs)
Dan Hendrycks and Kevin Gimpel · 2016
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A deep learning framework for character motion synthesis and editing
Daniel Holden, Jun Saito, and Taku Komura · 2016
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NTU RGB+D: A large scale dataset for 3d human activity analysis
Amir Shahroudy, Jun Liu, Tian-Tsong Ng, and Gang Wang · 2016
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A recurrent variational autoencoder for human motion synthesis
Ikhsanul Habibie, Daniel Holden, Jonathan Schwarz, Joe Yearsley, and Taku Komura · 2017
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beta-VAE: Learning basic visual concepts with a constrained variational framework
Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matt Botvinick, Shakir Mohamed, and Alexander Lerchner · 2017
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Phase-functioned neural networks for character control
Daniel Holden, Taku Komura, and Jun Saito · 2017
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On human motion prediction using recurrent neural networks
Julieta Martinez, Michael J. Black, and Javier Romero · 2017
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Embodied hands: Modeling and capturing hands and bodies together
Javier Romero, Dimitrios Tzionas, and Michael J. Black · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Text2Action: Generative adversarial synthesis from language to action
Hyemin Ahn, Timothy Ha, Yunho Choi, Hwiyeon Yoo, and Songhwai Oh · 2018
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HP-GAN: Probabilistic 3D human motion prediction via GAN
Emad Barsoum, John Kender, and Zicheng Liu · 2018
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Deep video generation, prediction and completion of human action sequences
Haoye Cai, Chunyan Bai, Yu-Wing Tai, and Chi-Keung Tang · 2018
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A large-scale RGB-D database for arbitrary-view human action recognition
Yanli Ji, Feixiang Xu, Yang Yang, Fumin Shen, Heng Tao Shen, and Wei-Shi Zheng · 2018
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Interactive character animation by learning multi-objective control
Kyungho Lee, Seyoung Lee, and Jehee Lee · 2018
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Action2motion: Conditioned generation of 3d human motions
Chuan Guo, Xinxin Zuo, Sen Wang, Shihao Zou, Qingyao Sun, Annan Deng, Minglun Gong, and Li Cheng · 2020
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Robust motion in-betweening
Félix G. Harvey, Mike Yurick, Derek Nowrouzezahrai, and C. 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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Learned motion matching
Daniel Holden, Oussama Kanoun, Maksym Perepichka, and Tiberiu Popa · 2020
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Transformer VAE: A hierarchical model for structure-aware and interpretable music representation learning
Junyan Jiang, Gus G. Xia, Dave B. Carlton, Chris N. Anderson, and Ryan H. Miyakawa · 2020
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Accelerating 3D deep learning with PyTorch3D
Justin Johnson, Nikhila Ravi, Jeremy Reizenstein, David Novotny, Shubham Tulsiani, Christoph Lassner, and Steve Branson · 2020
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Dario Pavllo, David Grangier, and Michael Auli · 2018
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STAR: Sparse trained articulated human body regressor
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Weakly supervised 3d human pose and shape reconstruction with normalizing flows
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Perpetual motion: Generating unbounded human motion
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Bayesian adversarial human motion synthesis
Rui Zhao, Hui Su, and Qiang Ji · 2020
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3D human shape reconstruction from a polarization image
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