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Following the success of deep convolutional networks, state-of-the-art methods for 3d human pose estimation have focused on deep end-to-end systems that predict 3d joint locations given raw image pixels.
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J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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X. K. Wei and J. Chai · 2009
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Twin Gaussian processes for structured prediction
L. Bo and C. Sminchisescu · 2010
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3d human pose reconstruction using millions of exemplars
H. Jiang · 2010
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Humaneva: Synchronized video and motion capture dataset and baseline algorithm for evaluation of articulated human motion
L. Sigal, A. O. Balan, and M. J. Black · 2010
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Reconstructing 3D Human Pose from 2D Image Landmarks
V. Ramakrishna, T. Kanade, and Y. Sheikh · 2012
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Monocular image 3d human pose estimation under self-occlusion
I. Radwan, A. Dhall, and R. Goecke · 2013
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A joint model for 2d and 3d pose estimation from a single image
E. Simo-Serra, A. Quattoni, C. Torras, and F. Moreno-Noguer · 2013
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2d human pose estimation: New benchmark and state of the art analysis
M. Andriluka, L. Pishchulin, P. Gehler, and B. Schiele · 2014
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3D Pose from Motion for Cross-view Action Recognition via Non-linear Circulant Temporal Encoding
Marker-less 3d human motion capture with monocular image sequence and height-maps
Y. Du, Y. Wong, Y. Liu, F. Han, Y. Gui, Z. Wang, M. Kankanhalli, and W. Geng · 2016
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Learning camera viewpoint using cnn to improve 3d body pose estimation
M. F. Ghezelghieh, R. Kasturi, and S. Sarkar · 2016
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Stacked hourglass networks for human pose estimation
A. Newell, K. Yang, and J. Deng · 2016
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3d human pose estimation using convolutional neural networks with 2d pose information
S. Park, J. Hwang, and N. Kwak · 2016
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Mocap-guided data augmentation for 3D pose estimation in the wild
G. Rogez and C. Schmid · 2016
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A. Gupta, J. Martinez, J. J. Little, and R. J. Woodham · 2014
Cited alongside, same era.
Iterated second-order label sensitive pooling for 3d human pose estimation
C. Ionescu, J. Carreira, and C. Sminchisescu · 2014
Cited alongside, same era.
Human 3.6m: Large scale datasets and predictive methods for 3d human sensing in natural environments
C. Ionescu, D. Papava, V. Olaru, and C. Sminchisescu · 2014
Cited alongside, same era.
Depth sweep regression forests for estimating 3d human pose from images
I. Kostrikov and J. Gall · 2014
Cited alongside, same era.
Dropout: a simple way to prevent neural networks from overfitting
N. Srivastava, G. E. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov · 2014
Cited alongside, same era.
Robust estimation of 3d human poses from a single image
C. Wang, Y. Wang, Z. Lin, A. L. Yuille, and W. Gao · 2014
Cited alongside, same era.
Pose-conditioned joint angle limits for 3D human pose reconstruction
I. Akhter and M. J. Black · 2015
Cited alongside, same era.
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Structured prediction of 3d human pose with deep neural networks
B. Tekin, I. Katircioglu, M. Salzmann, V. Lepetit, and P. Fua · 2016
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Direct prediction of 3d body poses from motion compensated sequences
B. Tekin, A. Rozantsev, V. Lepetit, and P. Fua · 2016
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Convolutional pose machines
S.-E. Wei, V. Ramakrishna, T. Kanade, and Y. Sheikh · 2016
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A dual-source approach for 3d pose estimation from a single image
H. Yasin, U. Iqbal, B. Kruger, A. Weber, and J. Gall · 2016
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Deep kinematic pose regression
X. Zhou, X. Sun, W. Zhang, S. Liang, and Y. Wei · 2016
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Sparse representation for 3d shape estimation: A convex relaxation approach
X. Zhou, M. Zhu, S. Leonardos, and K. Daniilidis · 2016
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Sparseness meets deepness: 3d human pose estimation from monocular video
X. Zhou, M. Zhu, S. Leonardos, K. G. Derpanis, and K. Daniilidis · 2016
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3D human pose estimation = 2D pose estimation + matching
C.-H. Chen and D. Ramanan · 2017
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3d human pose estimation from a single image via distance matrix regression
F. Moreno-Noguer · 2017
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Coarse-to-fine volumetric prediction for single-image 3D human pose
G. Pavlakos, X. Zhou, K. G. Derpanis, and K. Daniilidis · 2017
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Deep Multitask Architecture for Integrated 2D and 3D Human Sensing
A. Popa, M. Zanfir, and C. Sminchisescu · 2017
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Learning from simulated and unsupervised images through adversarial training
A. Shrivastava, T. Pfister, O. Tuzel, J. Susskind, W. Wang, and R. Webb · 2017
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Learning from synthetic humans
G. Varol, J. Romero, X. Martin, N. Mahmood, M. J. Black, I. Laptev, and C. Schmid · 2017
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