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We propose the Encoder-Recurrent-Decoder (ERD) model for recognition and prediction of human body pose in videos and motion capture.
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Gaussian process dynamical models
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The recurrent temporal restricted boltzmann machine
I. Sutskever, G. E. Hinton, and G. W. Taylor · 2008
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Topologically-constrained latent variable models
R. Urtasun, D. J. Fleet, A. Geiger, J. Popovic, T. Darrell, and N. D. Lawrence · 2008
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Gaussian process dynamical models for human motion
J. M. Wang, D. J. Fleet, and A. Hertzmann · 2008
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You’ll never walk alone: Modeling social behavior for multi-target tracking
S. Pellegrini, A. Ess, K. Schindler, and L. J. V. Gool · 2009
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Factored conditional restricted boltzmann machines for modeling motion style
G. W. Taylor and G. E. Hinton · 2009
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Bayesian nonparametric methods for learning Markov switching processes
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C. Desai and D. Ramanan · 2012
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A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Loose-limbed people: Estimating 3D human pose and motion using non-parametric belief propagation
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A. Graves · 2013
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Caffe: An open source convolutional architecture for fast feature embedding, 2013
Y. Jia · 2013
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Anticipating human activities for reactive robotic response
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Dynamical binary latent variable models for 3d human pose tracking
G. W. Taylor, L. Sigal, D. J. Fleet, and G. E. Hinton · 2010
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Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
P. Vincent, H. Larochelle, I. Lajoie, Y. Bengio, and P.-A. Manzagol · 2010
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Multi-hypothesis motion planning for visual object tracking
H. Gong, J. Simy, M. Likhachev, and J. Shi · 2011
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Recurrent neural network based language modeling in meeting recognition
S. Kombrink, T. Mikolov, M. Karafiát, and L. Burget · 2011
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N-best maximal decoders for part models
D. Park and D. Ramanan · 2011
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Parsing human motion with stretchable models
B. Sapp, D. Weiss, and B. Taskar · 2011
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H. S. Koppula and A. Saxena · 2013
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Modec:multimodal decomposable models for human pose estimation
B. Sapp and B. Taskar · 2013
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Deeppose: Human pose estimation via deep neural networks
A. Toshev and C. Szegedy · 2013
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Long-term recurrent convolutional networks for visual recognition and description
J. Donahue, L. A. Hendricks, S. Guadarrama, M. Rohrbach, S. Venugopalan, K. Saenko, and T. Darrell · 2014
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Human3.6m: Large scale datasets and predictive methods for 3d human sensing in natural environments
C. Ionescu, D. Papava, V. Olaru, and C. Sminchisescu · 2014
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Modeep: A deep learning framework using motion features for human pose estimation
A. Jain, J. Tompson, Y. LeCun, and C. Bregler · 2014
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Video (language) modeling: a baseline for generative models of natural videos
M. Ranzato, A. Szlam, J. Bruna, M. Mathieu, R. Collobert, and S. Chopra · 2014
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Sequence to sequence learning with neural networks
I. Sutskever, O. Vinyals, and Q. V. Le · 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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Show and tell: A neural image caption generator
O. Vinyals, A. Toshev, S. Bengio, and D. Erhan · 2014
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Viewpoints and keypoints
S. Tulsiani and J. Malik · 2015
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