Fetching the paper…
Reading the bibliography…
In this paper, we propose an end-to-end trainable regression approach for human pose estimation from still images.
Pictorial structures for object recognition
P. F. Felzenszwalb and D. P. Huttenlocher · 2005
Earlier work this paper cites.
Pictorial structures revisited: People detection and articulated pose estimation
M. Andriluka, S. Roth, and B. Schiele · 2009
Earlier work this paper cites.
Clustered pose and nonlinear appearance models for human pose estimation
S. Johnson and M. Everingham · 2010
Earlier work this paper cites.
Latent structured models for human pose estimation
C. Ionescu, F. Li, and C. Sminchisescu · 2011
Earlier work this paper cites.
Recognizing proxemics in personal photos
Y. Yang, S. Baker, A. Kannan, and D. Ramanan · 2012
Earlier work this paper cites.
Human Pose Estimation Using Body Parts Dependent Joint Regressors
M. Dantone, J. Gall, C. Leistner, and L. V. Gool · 2013
Earlier work this paper cites.
Human pose estimation using a joint pixel-wise and part-wise formulation
L. Ladicky, P. H. S. Torr, and A. Zisserman · 2013
Earlier work this paper cites.
Poselet Conditioned Pictorial Structures
L. Pishchulin, M. Andriluka, P. Gehler, and B. Schiele · 2013
Earlier work this paper cites.
Strong appearance and expressive spatial models for human pose estimation
L. Pishchulin, M. Andriluka, P. V. Gehler, and B. Schiele · 2013
Earlier work this paper cites.
2D Human Pose Estimation: New Benchmark and State of the Art Analysis
M. Andriluka, L. Pishchulin, P. Gehler, and B. Schiele · 2014
Earlier work this paper cites.
Articulated pose estimation by a graphical model with image dependent pairwise relations
X. Chen and A. Yuille · 2014
Earlier work this paper cites.
Human Pose Estimation with Fields of Parts
M. Kiefel and P. V. Gehler · 2014
Earlier work this paper cites.
Multi-source deep learning for human pose estimation
W. Ouyang, X. Chu, and X. Wang · 2014
Earlier work this paper cites.
Deep convolutional neural networks for efficient pose estimation in gesture videos
T. Pfister, K. Simonyan, J. Charles, and A. Zisserman · 2014
Earlier work this paper cites.
Pose Machines: Articulated Pose Estimation via Inference Machines
V. Ramakrishna, D. Munoz, M. Hebert, A. J. Bagnell, and Y. Sheikh · 2014
Earlier work this paper cites.
Joint training of a convolutional network and a graphical model for human pose estimation
J. J. Tompson, A. Jain, Y. LeCun, and C. Bregler · 2014
Cited alongside, same era.
DeepPose: Human Pose Estimation via Deep Neural Networks
A. Toshev and C. Szegedy · 2014
Cited alongside, same era.
Robust optimization for deep regression
V. Belagiannis, C. Rupprecht, G. Carneiro, and N. Navab · 2015
Cited alongside, same era.
Combining local appearance and holistic view: Dual-source deep neural networks for human pose estimation
X. Fan, K. Zheng, Y. Lin, and S. Wang · 2015
Cited alongside, same era.
Flowing convnets for human pose estimation in videos
T. Pfister, J. Charles, and A. Zisserman · 2015
Cited alongside, same era.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2015
Bottom-up and top-down reasoning with convolutional latent-variable models
P. Hu and D. Ramanan · 2016
Later among the works it cites.
DeeperCut: A Deeper, Stronger, and Faster Multi-Person Pose Estimation Model
E. Insafutdinov, L. Pishchulin, B. Andres, M. Andriluka, and B. Schiele · 2016
Later among the works it cites.
Human Pose Estimation Using Deep Consensus Voting
I. Lifshitz, E. Fetaya, and S. Ullman · 2016
Later among the works it cites.
Stacked Hourglass Networks for Human Pose Estimation
A. Newell, K. Yang, and J. Deng · 2016
Later among the works it cites.
DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation
L. Pishchulin, E. Insafutdinov, S. Tang, B. Andres, M. Andriluka, P. Gehler, and B. Schiele · 2016
Later among the works it cites.
An efficient convolutional network for human pose estimation
U. Rafi, I. Kostrikov, J. Gall, and B. Leibe · 2016
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Efficient object localization using Convolutional Networks
J. Tompson, R. Goroshin, A. Jain, Y. LeCun, and C. Bregler · 2015
Cited alongside, same era.
Recurrent human pose estimation
V. Belagiannis and A. Zisserman · 2016
Cited alongside, same era.
Human pose estimation via Convolutional Part Heatmap Regression
A. Bulat and G. Tzimiropoulos · 2016
Cited alongside, same era.
Human pose estimation with iterative error feedback
J. Carreira, P. Agrawal, K. Fragkiadaki, and J. Malik · 2016
Cited alongside, same era.
Xception: Deep learning with depthwise separable convolutions
F. Chollet · 2016
Cited alongside, same era.
Structured feature learning for pose estimation
X. Chu, W. Ouyang, H. Li, and X. Wang · 2016
Cited alongside, same era.
Later among the works it cites.
Inception-v4, inception-resnet and the impact of residual connections on learning
C. Szegedy, S. Ioffe, and V. Vanhoucke · 2016
Later among the works it cites.
Convolutional pose machines
S.-E. Wei, V. Ramakrishna, T. Kanade, and Y. Sheikh · 2016
Later among the works it cites.
End-to-end learning of deformable mixture of parts and deep convolutional neural networks for human pose estimation
W. Yang, W. Ouyang, H. Li, and X. Wang · 2016
Later among the works it cites.
Deep Deformation Network for Object Landmark Localization
X. Yu, F. Zhou, and M. Chandraker · 2016
Later among the works it cites.
Adversarial posenet: A structure-aware convolutional network for human pose estimation
Y. Chen, C. Shen, X. Wei, L. Liu, and J. Yang · 2017
Closest in time.
Self adversarial training for human pose estimation
C. Chou, J. Chien, and H. Chen · 2017
Closest in time.
Multi-context attention for human pose estimation
X. Chu, W. Yang, W. Ouyang, C. Ma, A. L. Yuille, and X. Wang · 2017
Closest in time.
LCR-Net: Localization-Classification-Regression for Human Pose
G. Rogez, P. Weinzaepfel, and C. Schmid · 2017
Closest in time.
Compositional human pose regression
X. Sun, J. Shang, S. Liang, and Y. Wei · 2017
Closest in time.