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We explore the importance of spatial contextual information in human pose estimation.
The graph neural network model
F. Scarselli, M. Gori, A. C. Tsoi, M. Hagenbuchner, and G. Monfardini · 2009
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Clustered pose and nonlinear appearance models for human pose estimation
S. Johnson and M. Everingham · 2010
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Torch7: A matlab-like environment for machine learning
R. Collobert, K. Kavukcuoglu, and C. Farabet · 2011
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Learning hierarchical poselets for human parsing
Y. Wang, D. Tran, and Z. Liao · 2011
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Articulated pose estimation with flexible mixtures-of-parts
Y. Yang and D. Ramanan · 2011
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Recursive compositional models for vision: Description and review of recent work
L. L. Zhu, Y. Chen, and A. Yuille · 2011
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Exploring the spatial hierarchy of mixture models for human pose estimation
Y. Tian, C. L. Zitnick, and S. G. Narasimhan · 2012
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Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude
T. Tieleman and G. Hinton · 2012
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Spectral networks and locally connected networks on graphs
J. Bruna, W. Zaremba, A. Szlam, and Y. LeCun · 2013
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Adaptive occlusion state estimation for human pose tracking under self-occlusions
N.-G. Cho, A. L. Yuille, and S.-W. Lee · 2013
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Poselet conditioned pictorial structures
L. Pishchulin, M. Andriluka, P. Gehler, and B. Schiele · 2013
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Real-time human pose recognition in parts from single depth images
J. Shotton, T. Sharp, A. Kipman, A. Fitzgibbon, M. Finocchio, A. Blake, M. Cook, and R. Moore · 2013
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An approach to pose-based action recognition
C. Wang, Y. Wang, and A. L. Yuille · 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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Learning phrase representations using rnn encoder-decoder for statistical machine translation
K. Cho, B. Van Merriënboer, C. Gulcehre, D. Bahdanau, F. Bougares, H. Schwenk, and Y. Bengio · 2014
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An expressive deep model for human action parsing from a single image
Z. Liang, X. Wang, R. Huang, and L. Lin · 2014
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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
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Deeppose: Human pose estimation via deep neural networks
A. Toshev and C. Szegedy · 2014
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Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2014
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Convolutional networks on graphs for learning molecular fingerprints
D. K. Duvenaud, D. Maclaurin, J. Iparraguirre, R. Bombarell, T. Hirzel, A. Aspuru-Guzik, and R. P. Adams · 2015
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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
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Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
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Improved semantic representations from tree-structured long short-term memory networks
K. S. Tai, R. Socher, and C. D. Manning · 2015
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Efficient object localization using convolutional networks
J. Tompson, R. Goroshin, A. Jain, Y. LeCun, and C. Bregler · 2015
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Stacked hourglass networks for human pose estimation
A. Newell, K. Yang, and J. Deng · 2016
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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
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An efficient convolutional network for human pose estimation
U. Rafi, B. Leibe, J. Gall, and I. Kostrikov · 2016
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Convolutional pose machines
S.-E. Wei, V. Ramakrishna, T. Kanade, and Y. Sheikh · 2016
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Recurrent human pose estimation
V. Belagiannis and A. Zisserman · 2017
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Adversarial posenet: A structure-aware convolutional network for human pose estimation
Y. Chen, C. Shen, X.-S. Wei, L. Liu, and J. Yang · 2017
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B. Xiaohan Nie, C. Xiong, and S.-C. Zhu · 2015
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Human pose estimation via convolutional part heatmap regression
A. Bulat and G. Tzimiropoulos · 2016
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Human pose estimation with iterative error feedback
J. Carreira, P. Agrawal, K. Fragkiadaki, and J. Malik · 2016
Cited alongside, same era.
L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille · 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.
Crf-cnn: Modeling structured information in human pose estimation
X. Chu, W. Ouyang, X. Wang, et al · 2016
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Convolutional neural networks on graphs with fast localized spectral filtering
M. Defferrard, X. Bresson, and P. Vandergheynst · 2016
Cited alongside, same era.
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Self adversarial training for human pose estimation
C.-J. Chou, J.-T. Chien, and H.-T. Chen · 2017
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Multi-context attention for human pose estimation
X. Chu, W. Yang, W. Ouyang, C. Ma, A. L. Yuille, and X. Wang · 2017
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Mask r-cnn
K. He, G. Gkioxari, P. Dollár, and R. Girshick · 2017
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Densely connected convolutional networks
G. Huang, Z. Liu, K. Q. Weinberger, and L. van der Maaten · 2017
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Situation recognition with graph neural networks
R. Li, M. Tapaswi, R. Liao, J. Jia, R. Urtasun, and S. Fidler · 2017
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Feature pyramid networks for object detection
T.-Y. Lin, P. Dollár, R. Girshick, K. He, B. Hariharan, and S. Belongie · 2017
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Sgn: Sequential grouping networks for instance segmentation
S. Liu, J. Jia, S. Fidler, and R. Urtasun · 2017
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The more you know: Using knowledge graphs for image classification
K. Marino, R. Salakhutdinov, and A. Gupta · 2017
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3d graph neural networks for rgbd semantic segmentation
X. Qi, R. Liao, J. Jia, S. Fidler, and R. Urtasun · 2017
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Learning feature pyramids for human pose estimation
W. Yang, S. Li, W. Ouyang, H. Li, and X. Wang · 2017
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F. Yu, D. Wang, and T. Darrell · 2017
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Path aggregation network for instance segmentation
S. Liu, L. Qi, H. Qin, J. Shi, and J. Jia · 2018
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