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We propose a method for object-aware 3D egocentric pose estimation that tightly integrates kinematics modeling, dynamics modeling, and scene object information.
Estimating contact dynamics
M. Brubaker, L. Sigal, and David J. Fleet · 2009
Earlier work this paper cites.
Stable proportional-derivative controllers
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Mujoco: A physics engine for model-based control
E. Todorov, T. Erez, and Y. Tassa · 2012
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Video-based 3d motion capture through biped control
M. Vondrak, L. Sigal, J. Hodgins, and O. C. Jenkins · 2012
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Learning phrase representations using rnn encoder-decoder for statistical machine translation
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Catalin Ionescu, Dragos Papava, Vlad Olaru, and Cristian Sminchisescu · 2014
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3d human pose estimation from monocular images with deep convolutional neural network
Sijin Li and Antoni B. Chan · 2014
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Adam: A method for stochastic optimization
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Smpl: a skinned multi-person linear model
M. Loper, Naureen Mahmood, J. Romero, Gerard Pons-Moll, and Michael J. Black · 2015
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Federica Bogo, A. Kanazawa, Christoph Lassner, P. Gehler, J. Romero, and Michael J. Black · 2016
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Pybullet, a python module for physics simulation for games, robotics and machine learning
Erwin Coumans and Yunfei Bai · 2016
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Deep residual learning for image recognition
Kaiming He, X. Zhang, Shaoqing Ren, and Jian Sun · 2016
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Seeing invisible poses: Estimating 3d body pose from egocentric video
Hao Jiang and Kristen Grauman · 2016
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Egocap: Egocentric marker-less motion capture with two fisheye cameras
Helge Rhodin, Christian Richardt, Dan Casas, Eldar Insafutdinov, Mohammad Shafiei, Hans-Peter Seidel, Bernt Schiele, and Christian Theobalt · 2016
Earlier work this paper cites.
Structured prediction of 3d human pose with deep neural networks
Bugra Tekin, Isinsu Katircioglu, M. Salzmann, Vincent Lepetit, and P. Fua · 2016
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Proximal policy optimization algorithms
John Schulman, F. Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Physics-based motion capture imitation with deep reinforcement learning
N. Chentanez, M. Müller, M. Macklin, Viktor Makoviychuk, and S. Jeschke · 2018
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Densepose: Dense human pose estimation in the wild
Riza Alp Güler, N. Neverova, and I. Kokkinos · 2018
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Exploiting temporal information for 3d human pose estimation
Mir Rayat Imtiaz Hossain and J. Little · 2018
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End-to-end recovery of human shape and pose
A. Kanazawa, Michael J. Black, D. Jacobs, and Jitendra Malik · 2018
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Deepmimic: Example-guided deep reinforcement learning of physics-based character skills
Xue Bin Peng, Pieter Abbeel, Sergey Levine, and Michiel van de Panne · 2018
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Xue Bin Peng, Angjoo Kanazawa, Jitendra Malik, Pieter Abbeel, and Sergey Levine · 2018
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PWC-Net: CNNs for optical flow using pyramid, warping, and cost volume
Deqing Sun, Xiaodong Yang, Ming-Yu Liu, and Jan Kautz · 2018
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3d ego-pose estimation via imitation learning
Ye Yuan and Kris Kitani · 2018
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Learning to sit: Synthesizing human-chair interactions via hierarchical control
Ego-pose estimation and forecasting as real-time pd control
Ye Yuan and Kris Kitani · 2019
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Learning 3d human shape and pose from dense body parts
Hongwen Zhang, Jie Cao, Guo Lu, Wanli Ouyang, and Z. Sun · 2019
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Hierarchical kinematic human mesh recovery
Georgios V. Georgakis, Ren Li, Srikrishna Karanam, Terrence Chen, Jana Kosecka, and Ziyan Wu · 2020
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Optical non-line-of-sight physics-based 3d human pose estimation
Mariko Isogawa, Ye Yuan, Matthew O’Toole, and Kris M Kitani · 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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Yu-Wei Chao, Jimei Yang, Weifeng Chen, and Jia Deng · 2019
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In the wild human pose estimation using explicit 2d features and intermediate 3d representations
I. Habibie, W. Xu, D. Mehta, G. Pons-Moll, and C. Theobalt · 2019
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Learning predict-and-simulate policies from unorganized human motion data
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Reusable neural skill embeddings for vision-guided whole body movement and object manipulation
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Camera distance-aware top-down approach for 3d multi-person pose estimation from a single rgb image
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Character controllers using motion vaes
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Contact and human dynamics from monocular video
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Physcap: Physically plausible monocular 3d motion capture in real time
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A scalable approach to control diverse behaviors for physically simulated characters
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Residual force control for agile human behavior imitation and extended motion synthesis
Ye Yuan and Kris Kitani · 2020
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Video face manipulation detection through ensemble of cnns
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