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A key step towards understanding human behavior is the prediction of 3D human motion.
Discrete cosine transform
Nasir Ahmed, T. Natarajan, and Kamisetty R. Rao · 1974
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Two deterministic half-quadratic regularization algorithms for computed imaging
Pierre Charbonnier, Laure Blanc-Feraud, Gilles Aubert, and Michel Barlaud · 1994
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http://mocap.cs.cmu.edu/ , 2000
CMU graphics lab. CMU graphics lab motion capture database · 2000
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Learning and tracking cyclic human motion
Dirk Ormoneit, Hedvig Sidenbladh, Michael Black, and Trevor Hastie · 2000
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Animating by multi-level sampling
K. Pullen and C. Bregler · 2000
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Documentation mocap database HDM05
Meinard Müller, Tido Röder, Michael Clausen, Bernhard Eberhardt, Björn Krüger, and Andreas Weber · 2007
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HumanEva: Synchronized video and motion capture dataset and baseline algorithm for evaluation of articulated human motion
Leonid Sigal, Alexandru O Balan, and Michael J Black · 2010
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Bilinear spatiotemporal basis models
Ijaz Akhter, Tomas Simon, Sohaib Khan, Iain Matthews, and Yaser Sheikh · 2012
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Learning phrase representations using RNN encoder–decoder for statistical machine translation
Kyunghyun Cho, Bart van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, 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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Mosh: Motion and shape capture from sparse markers
Matthew Loper, Naureen Mahmood, and Michael J Black · 2014
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Discrete cosine transform: algorithms, advantages, applications
K Ramamohan Rao and Ping Yip · 2014
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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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Keep it SMPL: Automatic estimation of 3D human pose and shape from a single image
Federica Bogo, Angjoo Kanazawa, Christoph Lassner, Peter Gehler, Javier Romero, and Michael J. Black · 2016
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Deep unsupervised clustering with gaussian mixture variational autoencoders
Nat Dilokthanakul, Pedro AM Mediano, Marta Garnelo, Matthew CH Lee, Hugh Salimbeni, Kai Arulkumaran, and Murray Shanahan · 2016
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Spectral style transfer for human motion between independent actions
M Ersin Yumer and Niloy J Mitra · 2016
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Learning human motion models for long-term predictions
Partha Ghosh, Jie Song, Emre Aksan, and Otmar Hilliges · 2017
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DeLiGAN: Generative adversarial networks for diverse and limited data
Swaminathan Gurumurthy, Ravi Kiran Sarvadevabhatla, and R Venkatesh Babu · 2017
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Motion database of disguised and non-disguised team handball penalty throws by novice and expert performers
Fabian Helm, Nikolaus F Troje, and Jörn Munzert · 2017
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Fast neural style transfer for motion data
Daniel Holden, Ikhsanul Habibie, Ikuo Kusajima, and Taku Komura · 2017
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Towards accurate marker-less human shape and pose estimation over time
Yinghao Huang, Federica Bogo, Christoph Lassner, Angjoo Kanazawa, Peter V Gehler, Javier Romero, Ijaz Akhter, and Michael J Black · 2017
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Human motion prediction for human-robot collaboration
Hongyi Liu and Lihui Wang · 2017
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On human motion prediction using recurrent neural networks
Julieta Martinez, Michael J Black, and Javier Romero · 2017
Cited alongside, same era.
Embodied Hands: Modeling and capturing hands and bodies together
Javier Romero, Dimitrios Tzionas, and Michael J. Black · 2017
Cited alongside, same era.
The pose knows: Video forecasting by generating pose futures
Jacob Walker, Kenneth Marino, Abhinav Gupta, and Martial Hebert · 2017
Cited alongside, same era.
https://accad.osu.edu/research/motion-lab/systemdata , 2018
ACCAD MoCap System and Data · 2018
Expressive body capture: 3D hands, face, and body from a single image
Georgios Pavlakos, Vasileios Choutas, Nima Ghorbani, Timo Bolkart, Ahmed A. A. Osman, Dimitrios Tzionas, and Michael J. Black · 2019
Later among the works it cites.
Modeling human motion with quaternion-based neural networks
Dario Pavllo, Christoph Feichtenhofer, Michael Auli, and David Grangier · 2019
Later among the works it cites.
Predicting 3D human dynamics from video
Jason Y Zhang, Panna Felsen, Angjoo Kanazawa, and Jitendra Malik · 2019
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On the continuity of rotation representations in neural networks
Yi Zhou, Connelly Barnes, Jingwan Lu, Jimei Yang, and Hao Li · 2019
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Attention, please: A spatio-temporal transformer for 3D human motion prediction
Emre Aksan, Peng Cao, Manuel Kaufmann, and Otmar Hilliges · 2020
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Cited alongside, same era.
HP-GAN: Probabilistic 3D human motion prediction via GAN
Emad Barsoum, John Kender, and Zicheng Liu · 2018
Cited alongside, same era.
Accurate and diverse sampling of sequences based on a “best of many” sample objective
Apratim Bhattacharyya, Bernt Schiele, and Mario Fritz · 2018
Cited alongside, same era.
Adversarial geometry-aware human motion prediction
Liang-Yan Gui, Yu-Xiong Wang, Xiaodan Liang, and José MF Moura · 2018
Cited alongside, same era.
Few-shot human motion prediction via meta-learning
Liang-Yan Gui, Yu-Xiong Wang, Deva Ramanan, and José MF Moura · 2018
Cited alongside, same era.
Convolutional sequence to sequence model for human dynamics
Chen Li, Zhen Zhang, Wee Sun Lee, and Gim Hee Lee · 2018
Cited alongside, same era.
Quaternet: A quaternion-based recurrent model for human motion
Dario Pavllo, David Grangier, and Michael Auli · 2018
Cited alongside, same era.
Yujun Cai, Lin Huang, Yiwei Wang, Tat-Jen Cham, Jianfei Cai, Junsong Yuan, Jun Liu, Xu Yang, Yiheng Zhu, Xiaohui Shen, et al · 2020
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Learning dynamic relationships for 3D human motion prediction
Qiongjie Cui, Huaijiang Sun, and Fei Yang · 2020
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Integrating situational probability and kinematic information when anticipating disguised movements
Fabian Helm, Rouwen Cañal-Bruland, David L Mann, Nikolaus F Troje, and Jörn Munzert · 2020
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VIBE: Video inference for human body pose and shape estimation
Muhammed Kocabas, Nikos Athanasiou, and Michael J. Black · 2020
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Dynamic multiscale graph neural networks for 3D skeleton based human motion prediction
Maosen Li, Siheng Chen, Yangheng Zhao, Ya Zhang, Yanfeng Wang, and Qi Tian · 2020
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Character controllers using motion VAEs
Hung Yu Ling, Fabio Zinno, George Cheng, and Michiel Van De Panne · 2020
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STAR: Sparse trained articulated human body regressor
Ahmed A. A. Osman, Timo Bolkart, and Michael J. Black · 2020
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Human motion trajectory prediction: A survey
Andrey Rudenko, Luigi Palmieri, Michael Herman, Kris M Kitani, Dariu M Gavrila, and Kai O Arras · 2020
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History repeats itself: Human motion prediction via motion attention
Mao Wei, Liu Miaomiao, and Salzemann Mathieu · 2020
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4D Forecasting: Sequantial Forecasting of 100,000 Points
Xinshuo Weng, Jianren Wang, Sergey Levine, Kris Kitani, and Nick Rhinehart · 2020
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Inverting the Pose Forecasting Pipeline with SPF2: Sequential Pointcloud Forecasting for Sequential Pose Forecasting
Xinshuo Weng, Jianren Wang, Sergey Levine, Kris Kitani, and Nick Rhinehart · 2020
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Futurepong: Real-time table tennis trajectory forecasting using pose prediction network
Erwin Wu and Hideki Koike · 2020
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GHUM & GHUML: Generative 3D human shape and articulated pose models
Hongyi Xu, Eduard Gabriel Bazavan, Andrei Zanfir, William T Freeman, Rahul Sukthankar, and Cristian Sminchisescu · 2020
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DLow: Diversifying latent flows for diverse human motion prediction
Ye Yuan and Kris Kitani · 2020
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Diverse trajectory forecasting with determinantal point processes
Ye Yuan and Kris M. Kitani · 2020
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Perpetual motion: Generating unbounded human motion
Yan Zhang, Michael J Black, and Siyu Tang · 2020
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