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Traditionally, monocular 3D human pose estimation employs a machine learning model to predict the most likely 3D pose for a given input image.
Mixture density networks
Christopher M. Bishop · 1994
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Covariance scaled sampling for monocular 3d body tracking
Cristian Sminchisescu and Bill Triggs · 2001
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Kinematic jump processes for monocular 3d human tracking
Cristian Sminchisescu and Bill Triggs · 2003
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Proposal maps driven mcmc for estimating human body pose in static images
Mun Wai Lee and Isaac Cohen · 2004
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Learning effective human pose estimation from inaccurate annotation
Sam Johnson and Mark Everingham · 2011
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Single image 3d human pose estimation from noisy observations
E. Simo-Serra, A. Ramisa, G. Alenyà, C. Torras, and F. Moreno-Noguer · 2012
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2d human pose estimation: New benchmark and state of the art analysis
Mykhaylo Andriluka, Leonid Pishchulin, Peter Gehler, and Bernt Schiele · 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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Pose-conditioned joint angle limits for 3d human pose reconstruction
Ijaz Akhter and Michael J. Black · 2015
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Unbiased decoding of biologically motivated visual feature descriptors
Michael Felsberg, Kristoffer Öfjäll, and Reiner Lenz · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 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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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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3d human pose estimation = 2d pose estimation + matching
Ching-Hang Chen and Deva Ramanan · 2017
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Generating multiple diverse hypotheses for human 3d pose consistent with 2d joint detections
Ehsan Jahangiri and Alan L. Yuille · 2017
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A simple yet effective baseline for 3d human pose estimation
Julieta Martinez, Rayat Hossain, Javier Romero, and James J. Little · 2017
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Monocular 3d human pose estimation in the wild using improved cnn supervision
Dushyant Mehta, Helge Rhodin, Dan Casas, Pascal Fua, Oleksandr Sotnychenko, Weipeng Xu, and Christian Theobalt · 2017
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3d human pose estimation from a single image via distance matrix regression
Francesc Moreno-Noguer · 2017
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Learning pose grammar to encode human body configuration for 3d pose estimation
Haoshu Fang, Yuanlu Xu, Wenguan Wang, Xiaobai Liu, and Song-Chun Zhu · 2018
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Exploiting temporal information for 3d pose estimation
Mir Rayat Imtiaz Hossain and James J. Little · 2018
Cited alongside, same era.
End-to-end recovery of human shape and pose
Angjoo Kanazawa, Michael J. Black, David W. Jacobs, and Jitendra Malik · 2018
Cited alongside, same era.
Vibe: Video inference for human body pose and shape estimation
Georgios Pavlakos, Luyang Zhu, Xiaowei Zhou, and Kostas Daniilidis · 2018
Cited alongside, same era.
Optimizing network structure for 3d human pose estimation
Hai Ci, Chunyu Wang, Xiaoxuan Ma, and Yizhou Wang · 2019
Cited alongside, same era.
In the wild human pose estimation using explicit 2d features and intermediate 3d representations
Ikhsanul Habibie, Weipeng Xu, Dushyant Mehta, Gerard Pons-Moll, and Christian Theobalt · 2019
Cited alongside, same era.
Learning to reconstruct 3d human pose and shape via model-fitting in the loop
Nikos Kolotouros, Georgios Pavlakos, Michael J. Black, and Kostas Daniilidis · 2019
Graphmdn: Leveraging graph structure and deep learning to solve inverse problems
Tuomas P. Oikarinen, Daniel C. Hannah, and Sohrob Kazerounian · 2020
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Physcap: Physically plausible monocular 3d motion capture in real time
Soshi Shimada, Vladislav Golyanik, Weipeng Xu, and Christian Theobalt · 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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Deep kinematics analysis for monocular 3d human pose estimation
Jingwei Xu, Zhenbo Yu, Bingbing Ni, Jiancheng Yang, Xiaokang Yang, and Wenjun Zhang · 2020
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Weakly supervised 3d human pose and shape reconstruction with normalizing flows
Andrei Zanfir, Eduard Gabriel Bazavan, Hongyi Xu, Bill Freeman, Rahul Sukthankar, and Cristian Sminchisescu · 2020
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Cited alongside, same era.
Generating multiple hypotheses for 3d human pose estimation with mixture density network
Chen Li and Gim Hee Lee · 2019
Cited alongside, same era.
Monocular 3d human pose estimation by generation and ordinal ranking
Saurabh Sharma, Pavan Teja Varigonda, Prashast Bindal, Abhishek Sharma, and Arjun Jain · 2019
Cited alongside, same era.
Deep high-resolution representation learning for human pose estimation
Ke Sun, Bin Xiao, Dong Liu, and Jingdong Wang · 2019
Cited alongside, same era.
Repnet: Weakly supervised training of an adversarial reprojection network for 3d human pose estimation
Bastian Wandt and Bodo Rosenhahn · 2019
Cited alongside, same era.
Not all parts are created equal: 3d pose estimation by modelling bi-directional dependencies of body parts
Jue Wang, Shaoli Huang, Xinchao Wang, and Dacheng Tao · 2019
Cited alongside, same era.
Semantic graph convolutional networks for 3d human pose regression
Long Zhao, Xi Peng, Yu Tian, Mubbasir Kapadia, and Dimitris N. Metaxas · 2019
Cited alongside, same era.
Probabilistic modeling for human mesh recovery
Nikos Kolotouros, Georgios Pavlakos, Dinesh Jayaraman, and Kostas Daniilidis · 2021
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Hybrik: A hybrid analytical-neural inverse kinematics solution for 3d human pose and shape estimation
Jiefeng Li, Chao Xu, Zhicun Chen, Siyuan Bian, Lixin Yang, and Cewu Lu · 2021
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Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
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D2c: Diffusion-decoding models for few-shot conditional generation
Abhishek Sinha, Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
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Csdi: Conditional score-based diffusion models for probabilistic time series imputation
Yusuke Tashiro, Jiaming Song, Yang Song, and Stefano Ermon · 2021
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Canonpose: Self-supervised monocular 3d human pose estimation in the wild
Bastian Wandt, Marco Rudolph, Petrissa Zell, Helge Rhodin, and Bodo Rosenhahn · 2021
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Probabilistic monocular 3d human pose estimation with normalizing flows
Tom Wehrbein, Marco Rudolph, Bodo Rosenhahn, and Bastian Wandt · 2021
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Adversarial parametric pose prior
Andrey Davydov, Anastasia Remizova, Victor Constantin, Sina Honari, Mathieu Salzmann, and Pascal Fua · 2022
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Mhformer: Multi-hypothesis transformer for 3d human pose estimation
Wenhao Li, Hong Liu, Hao Tang, Pichao Wang, and Luc Van Gool · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S Sara Mahdavi, Rapha Gontijo Lopes, et al · 2022
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Elepose: Unsupervised 3d human pose estimation by predicting camera elevation and learning normalizing flows on 2d poses
Bastian Wandt, James J Little, and Helge Rhodin · 2022
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