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Despite of the recent success of neural networks for human pose estimation, current approaches are limited to pose estimation of a single person and cannot handle humans in groups or crowds.
Learning long-term dependencies with gradient descent is difficult
Bengio, Y., Simard, P., Frasconi, P.: · 1994
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Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods
Platt, J.C.: · 1999
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Pictorial structures for object recognition
Felzenszwalb, P.F., Huttenlocher, D.P.: · 2005
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We are family: Joint pose estimation of multiple persons
Eichner, M., Ferrari, V.: · 2010
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Improved human parsing with a full relational model
Tran, D., Forsyth, D.: · 2010
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Understanding the difficulty of training deep feedforward neural networks
Glorot, X., Bengio, Y.: · 2010
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Clustered pose and nonlinear appearance models for human pose estimation
Johnson, S., Everingham, M.: · 2010
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Articulated part-based model for joint object detection and pose estimation
Sun, M., Savarese, S.: · 2011
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LIBSVM: A library for support vector machines
Chang, C.C., Lin, C.J.: · 2011
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Articulated people detection and pose estimation: Reshaping the future
Pishchulin, L., Jain, A., Andriluka, M., Thormählen, T., Schiele, B.: · 2012
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Discriminative appearance models for pictorial structures
Andriluka, M., Roth, S., Schiele, B.: · 2012
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Human pose estimation using a joint pixel-wise and part-wise formulation
Ladicky, L., Torr, P.H., Zisserman, A.: · 2013
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Poselet conditioned pictorial structures
Pishchulin, L., Andriluka, M., Gehler, P., Schiele, B.: · 2013
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Beyond physical connections: Tree models in human pose estimation
Wang, F., Li, Y.: · 2013
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Articulated human detection with flexible mixtures of parts
Yang, Y., Ramanan, D.: · 2013
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Human pose estimation using a joint pixel-wise and part-wise formulation
Ladicky, L., Torr, P., Zisserman, A.: · 2013
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Articulated pose estimation by a graphical model with image dependent pairwise relations
Chen, X., Yuille, A.L.: · 2014
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Parsing occluded people by flexible compositions
Chen, X., Yuille, A.L.: · 2015
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3d pictorial structures revisited: Multiple human pose estimation
Belagiannis, V., Amin, S., Andriluka, M., Schiele, B., Navab, N., Ilic, S.: · 2015
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Faster R-CNN: Towards real-time object detection with region proposal networks
Ren, S., He, K., Girshick, R., Sun, J.: · 2015
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The PASCAL visual object classes challenge: A retrospective
Everingham, M., Eslami, S.M.A., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman, A.: · 2015
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Human pose estimation with iterative error feedback
Carreira, J., Agrawal, P., Fragkiadaki, K., Malik, J.: · 2016
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Deepcut: Joint subset partition and labeling for multi person pose estimation
Pishchulin, L., Insafutdinov, E., Tang, S., Andres, B., Andriluka, M., Gehler, P., Schiele, B.: · 2016
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Joint training of a convolutional network and a graphical model for human pose estimation
Tompson, J., Jain, A., LeCun, Y., Bregler, C.: · 2014
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Using k-poselets for detecting people and localizing their keypoints
Gkioxari, G., Hariharan, B., Girshick, R., Malik, J.: · 2014
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2d human pose estimation: New benchmark and state of the art analysis
Andriluka, M., Pishchulin, L., Gehler, P., Schiele, B.: · 2014
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Body parts dependent joint regressors for human pose estimation in still images
Dantone, M., Leistner, C., Gall, J., Van Gool, L.: · 2014
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Efficient object localization using convolutional networks
Tompson, J., Goroshin, R., Jain, A., LeCun, Y., Bregler, C.: · 2015
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Convolutional pose machines
Wei, S.E., Ramakrishna, V., Kanade, T., Sheikh, Y.: · 2016
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Deepercut: A deeper, stronger, and faster multi-person pose estimation model
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Stacked hourglass networks for human pose estimation
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Human pose estimation via convolutional part heatmap regression
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