Fetching the paper…
Reading the bibliography…
One major challenge for monocular 3D human pose estimation in-the-wild is the acquisition of training data that contains unconstrained images annotated with accurate 3D poses.
2D human pose estimation: New benchmark and state of the art analysis
Mykhaylo Andriluka, Leonid Pishchulin, Peter Gehler, and Bernt Schiele · 2014
Earlier work this paper cites.
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
Earlier work this paper cites.
3D human pose estimation from monocular images with deep convolutional neural network
Sijin Li and Antoni B. Chan · 2014
Earlier work this paper cites.
Posebits for monocular human pose estimation
Gerard Pons-Moll, David J. Fleet, and Bodo Rosenhahn · 2014
Earlier work this paper cites.
Maximum-margin structured learning with deep networks for 3D human pose estimation
Sijin Li, Weichen Zhang, and Antoni Chan · 2015
Earlier work this paper cites.
Synthesizing training images for boosting human 3d pose estimation
W. Chen, H. Wang, Y. Li, H. Su, Z. Wang, C. Tu, D. Lischinski, D. Cohen-Or, and B. Chen · 2016
Earlier work this paper cites.
MoCap-guided data augmentation for 3D pose estimation in the wild
Grégory Rogez and Cordelia Schmid · 2016
Earlier work this paper cites.
Structured prediction of 3D human pose with deep neural networks
Bugra Tekin, Isinsu Katircioglu, Mathieu Salzmann, Vincent Lepetit, and Pascal Fua · 2016
Earlier work this paper cites.
Single image 3d interpreter network
Jiajun Wu, Tianfan Xue, Joseph J Lim, Yuandong Tian, Joshua B Tenenbaum, Antonio Torralba, and William T Freeman · 2016
Earlier work this paper cites.
Deep kinematic pose regression
Xingyi Zhou, Xiao Sun, Wei Zhang, Shuang Liang, and Yichen Wei · 2016
Earlier work this paper cites.
3D human pose estimation = 2D pose estimation + matching
Ching-Hang Chen and Deva Ramanan · 2017
Earlier work this paper cites.
A simple yet effective baseline for 3D human pose estimation
Julieta Martinez, Rayat Hossain, Javier Romero, and James J. Little · 2017
Earlier work this paper cites.
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
Earlier work this paper cites.
VNect: Real-time 3D human pose estimation with a single RGB camera
Dushyant Mehta, Srinath Sridhar, Oleksandr Sotnychenko, Helge Rhodin, Mohammad Shafiei, Hans-Peter Seidel, Weipeng Xu, Dan Casas, and Christian Theobalt · 2017
Earlier work this paper cites.
3D human pose estimation from a single image via distance matrix regression
F. Moreno-Noguer · 2017
Earlier work this paper cites.
Coarse-to-fine volumetric prediction for single-image 3D human pose
Georgios Pavlakos, Xiaowei Zhou, Konstantinos G Derpanis, and Kostas Daniilidis · 2017
Earlier work this paper cites.
Harvesting multiple views for marker-less 3d human pose annotations
Georgios Pavlakos, Xiaowei Zhou, Konstantinos G Derpanis, and Kostas Daniilidis · 2017
Earlier work this paper cites.
Deep multitask architecture for integrated 2D and 3D human sensing
Alin-Ionut Popa, Mihai Zanfir, and Cristian Sminchisescu · 2017
Earlier work this paper cites.
LCR-Net: Localization-classification-regression for human pose
Gregory Rogez, Philippe Weinzaepfel, and Cordelia Schmid · 2017
Cited alongside, same era.
Compositional human pose regression
Xiao Sun, Jiaxiang Shang, Shuang Liang, and Yichen Wei · 2017
Cited alongside, same era.
Lifting from the deep: Convolutional 3D pose estimation from a single image
Denis Tome, Chris Russell, and Lourdes Agapito · 2017
Cited alongside, same era.
Self-supervised learning of motion capture
Hsiao-Yu Tung, Wei Tung, Ersin Yumer, and Katerina Fragkiadaki · 2017
Cited alongside, same era.
Adversarial inverse graphics networks: Learning 2d-to-3d lifting and image-to-image translation from unpaired supervision
Hsiao-Yu Fish Tung, Adam W Harley, William Seto, and Katerina Fragkiadaki · 2017
Cited alongside, same era.
Learning from synthetic humans
Gül Varol, Javier Romero, Xavier Martin, Naureen Mahmood, Michael J. Black, Ivan Laptev, and Cordelia Schmid · 2017
Integral human pose regression
Xiao Sun, Bin Xiao, Shuang Liang, and Yichen Wei · 2018
Later among the works it cites.
Simple baselines for human pose estimation and tracking
B. Xiao, H. Wu, and Y. Wei · 2018
Later among the works it cites.
3d human pose estimation in the wild by adversarial learning
Wei Yang, Wanli Ouyang, Xiaolong Wang, Jimmy Ren, Hongsheng Li, and Xiaogang Wang · 2018
Later among the works it cites.
Exploiting temporal context for 3d human pose estimation in the wild
Anurag Arnab, Carl Doersch, and Andrew Zisserman · 2019
Later among the works it cites.
Unsupervised 3d pose estimation with geometric self-supervision
Ching-Hang Chen, Ambrish Tyagi, Amit Agrawal, Dylan Drover, Rohith MV, Stefan Stojanov, and James M. Rehg · 2019
Later among the works it cites.
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
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Towards 3d human pose estimation in the wild: a weakly-supervised approach
Xingyi Zhou, Qixing Huang, Xiao Sun, Xiangyang Xue, and Yichen Wei · 2017
Cited alongside, same era.
Learning 3d human pose from structure and motion
Rishabh Dabral, Anurag Mundhada, Uday Kusupati, Safeer Afaque, Abhishek Sharma, and Arjun Jain · 2018
Cited alongside, same era.
Can 3d pose be learned from 2d projections alone?
Dylan Drover, Rohith M. V, Ching-Hang Chen, Amit Agrawal, Ambrish Tyagi, and Cong Phuoc Huynh · 2018
Cited alongside, same era.
Exploiting temporal information for 3d pose estimation
Mir Rayat Imtiaz Hossain and James J. Little · 2018
Cited alongside, same era.
A dual-source approach for 3D pose estimation in single images
Umar Iqbal, Andreas Doering, Hashim Yasin, Björn Krüger, Andreas Weber, and Juergen Gall · 2018
Cited alongside, same era.
Hand pose estimation via 2.5D latent heatmap regression
Umar Iqbal, Pavlo Molchanov, Thomas Breuel, Juergen Gall, and Jan Kautz · 2018
Cited alongside, same era.
Later among the works it cites.
Self-supervised learning of 3d human pose using multi-view geometry
Muhammed Kocabas, Salih Karagoz, and Emre Akbas · 2019
Later among the works it cites.
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
Later among the works it cites.
Learning the depths of moving people by watching frozen people
Zhengqi Li, Tali Dekel, Forrester Cole, Richard Tucker, Noah Snavely, Ce Liu, and William T. Freeman · 2019
Later among the works it cites.
On boosting single-frame 3d human pose estimation via monocular videos
Zhi Li, Xuan Wang, Fei Wang, and Peilin Jiang · 2019
Later among the works it cites.
C3dpo: Canonical 3d pose networks for non-rigid structure from motion
David Novotny, Nikhila Ravi, Benjamin Graham, Natalia Neverova, and Andrea Vedaldi · 2019
Later among the works it cites.
Texturepose: Supervising human mesh estimation with texture consistency
Georgios Pavlakos, Nikos Kolotouros, and Kostas Daniilidis · 2019
Later among the works it cites.
3d human pose estimation in video with temporal convolutions and semi-supervised training
Dario Pavllo, Christoph Feichtenhofer, David Grangier, and Michael Auli · 2019
Later among the works it cites.
Deep high-resolution representation learning for human pose estimation
Ke Sun, Bin Xiao, Dong Liu, and Jingdong Wang · 2019
Later among the works it cites.
Repnet: Weakly supervised training of an adversarial reprojection network for 3d human pose estimation
Bastian Wandt and Bodo Rosenhahn · 2019
Later among the works it cites.
Distill knowledge from nrsfm for weakly supervised 3d pose learning
Chaoyang Wang, Chen Kong, and Simon Lucey · 2019
Later among the works it cites.
Monet: Multiview semi-supervised keypoint detection via epipolar divergence
Yuan Yao, Yasamin Jafarian, and Hyun Soo Park · 2019
Later among the works it cites.