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We present convolutional neural networks for the tasks of keypoint (pose) prediction and action classification of people in unconstrained images.
The representation and matching of pictorial structures
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Detecting people using mutually consistent poselet activations
L. Bourdev, S. Maji, T. Brox, and J. Malik · 2010
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The PASCAL Visual Object Classes (VOC) Challenge
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2010
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Object detection with discriminatively trained part based models
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B. Sapp, A. Toshev, and B. Taskar · 2010
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Action recognition from a distributed representation of pose and appearance
S. Maji, L. Bourdev, and J. Malik · 2011
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Learning hierarchical poselets for human parsing
Y. Wang, D. Tran, and Z. Liao · 2011
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http://pascallin.ecs.soton.ac.uk/challenges/voc/voc2012/, 2012
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ImageNet Large Scale Visual Recognition Competition 2012 (ILSVRC2012)
J. Deng, A. Berg, S. Satheesh, H. Su, A. Khosla, and L. Fei-Fei · 2012
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Articulated pose estimation using discriminative armlet classifiers
G. Gkioxari, P. Arbelaez, L. Bourdev, and J. Malik · 2013
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Poselet conditioned pictorial structures
L. Pishchulin, M. Andriluka, P. Gehler, and B. Schiele · 2013
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Multiscale combinatorial grouping
P. Arbeláez, J. Pont-Tuset, J. Barron, F. Marques, and J. Malik · 2014
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Rich feature hierarchies for accurate object detection and semantic segmentation
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Using k-poselets for detecting people and localizing their keypoints
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Integrating randomization and discrimination for classifying human-object interaction activities
A. Khosla, B. Yao, and L. Fei-Fei · 2014
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Decaf: A deep convolutional activation feature for generic visual recognition
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