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Existing pose estimation approaches fall into two categories: single-stage and multi-stage methods.
Pictorial structures revisited: People detection and articulated pose estimation
M. Andriluka, S. Roth, and B. Schiele · 2009
Earlier work this paper cites.
Adaptive pose priors for pictorial structures
B. Sapp, C. Jordan, and B. Taskar · 2010
Earlier work this paper cites.
Learning effective human pose estimation from inaccurate annotation
S. Johnson and M. Everingham · 2011
Earlier work this paper cites.
Articulated pose estimation with flexible mixtures-of-parts
Y. Yang and D. Ramanan · 2011
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Earlier work this paper cites.
Human pose estimation using body parts dependent joint regressors
M. Dantone, J. Gall, C. Leistner, and L. Van Gool · 2013
Earlier work this paper cites.
Articulated pose estimation using discriminative armlet classifiers
G. Gkioxari, P. Arbelaez, L. Bourdev, and J. Malik · 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.
Modec: Multimodal decomposable models for human pose estimation
B. Sapp and B. Taskar · 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.
Microsoft coco: Common objects in context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
Earlier work this paper cites.
Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
Earlier work this paper cites.
Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2015
Earlier work this paper cites.
Human pose estimation via convolutional part heatmap regression
A. Bulat and G. Tzimiropoulos · 2016
Earlier work this paper cites.
Realtime multi-person 2d pose estimation using part affinity fields
Z. Cao, T. Simon, S.-E. Wei, and Y. Sheikh · 2016
Earlier work this paper cites.
Human pose estimation with iterative error feedback
J. Carreira, P. Agrawal, K. Fragkiadaki, and J. Malik · 2016
Earlier work this paper cites.
Chained predictions using convolutional neural networks
G. Gkioxari, A. Toshev, and N. Jaitly · 2016
Cited alongside, same era.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Cited alongside, same era.
Deepercut: A deeper, stronger, and faster multi-person pose estimation model
E. Insafutdinov, L. Pishchulin, B. Andres, M. Andriluka, and B. Schiele · 2016
Cited alongside, same era.
Stacked hourglass networks for human pose estimation
A. Newell, K. Yang, and J. Deng · 2016
Cited alongside, same era.
Deepcut: Joint subset partition and labeling for multi person pose estimation
L. Pishchulin, E. Insafutdinov, S. Tang, B. Andres, M. Andriluka, P. V. Gehler, and B. Schiele · 2016
Cited alongside, same era.
Convolutional pose machines
S.-E. Wei, V. Ramakrishna, T. Kanade, and Y. Sheikh · 2016
Cited alongside, same era.
Associative embedding: End-to-end learning for joint detection and grouping
A. Newell, Z. Huang, and J. Deng · 2017
Later among the works it cites.
Towards accurate multi-person pose estimation in the wild
G. Papandreou, T. Zhu, N. Kanazawa, A. Toshev, J. Tompson, C. Bregler, and K. Murphy · 2017
Later among the works it cites.
Inception-v4, inception-resnet and the impact of residual connections on learning
C. Szegedy, S. Ioffe, V. Vanhoucke, and A. A. Alemi · 2017
Later among the works it cites.
Aggregated residual transformations for deep neural networks
S. Xie, R. Girshick, P. Dollár, Z. Tu, and K. He · 2017
Later among the works it cites.
Learning feature pyramids for human pose estimation
W. Yang, S. Li, W. Ouyang, H. Li, and X. Wang · 2017
Later among the works it cites.
Cascaded pyramid network for multi-person pose estimation
Y. Chen, Z. Wang, Y. Peng, Z. Zhang, G. Yu, and J. Sun · 2018
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Recurrent human pose estimation
V. Belagiannis and A. Zisserman · 2017
Cited alongside, same era.
Adversarial posenet: A structure-aware convolutional network for human pose estimation
Y. Chen, C. Shen, X.-S. Wei, L. Liu, and J. Yang · 2017
Cited alongside, same era.
Adversarial posenet: A structure-aware convolutional network for human pose estimation
Y. Chen, C. Shen, X.-S. Wei, L. Liu, and J. Yang · 2017
Cited alongside, same era.
Xception: Deep learning with depthwise separable convolutions
F. Chollet · 2017
Cited alongside, same era.
Self adversarial training for human pose estimation
C.-J. Chou, J.-T. Chien, and H.-T. Chen · 2017
Cited alongside, same era.
Multi-context attention for human pose estimation
X. Chu, W. Yang, W. Ouyang, C. Ma, A. L. Yuille, and X. Wang · 2017
Cited alongside, same era.
Later among the works it cites.
Multi-scale structure-aware network for human pose estimation
L. Ke, M.-C. Chang, H. Qi, and S. Lyu · 2018
Later among the works it cites.
Detnet: A backbone network for object detection
Z. Li, C. Peng, G. Yu, X. Zhang, Y. Deng, and J. Sun · 2018
Later among the works it cites.
Knowledge-guided deep fractal neural networks for human pose estimation
G. Ning, Z. Zhang, and Z. He · 2018
Later among the works it cites.
Megdet: A large mini-batch object detector
C. Peng, T. Xiao, Z. Li, Y. Jiang, X. Zhang, K. Jia, G. Yu, and J. Sun · 2018
Later among the works it cites.
Deeply learned compositional models for human pose estimation
W. Tang, P. Yu, and Y. Wu · 2018
Later among the works it cites.
Quantized densely connected u-nets for efficient landmark localization
Z. Tang, X. Peng, S. Geng, L. Wu, S. Zhang, and D. Metaxas · 2018
Later among the works it cites.
Quantized densely connected u-nets for efficient landmark localization
Z. Tang, X. Peng, S. Geng, L. Wu, S. Zhang, and D. Metaxas · 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.
Deep high-resolution representation learning for human pose estimation
K. Sun, B. Xiao, D. Liu, and J. Wang · 2019
Closest in time.
Human pose estimation with spatial contextual information
H. Zhang, H. Ouyang, S. Liu, X. Qi, X. Shen, R. Yang, and J. Jia · 2019
Closest in time.