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We propose a new architecture for the learning of predictive spatio-temporal motion models from data alone.
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Y. Bengio, L. Yao, G. Alain, and P. Vincent · 2013
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K. Fragkiadaki, H. Hu, and J. Shi · 2013
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C. Ionescu, D. Papava, V. Olaru, and C. Sminchisescu · 2014
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S. J. Rennie, V. Goel, and S. Thomas · 2014
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H. S. Koppula and A. Saxena · 2016
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J. Liu, A. Shahroudy, D. Xu, and G. Wang · 2016
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C. Mandery, Ö. Terlemez, M. Do, N. Vahrenkamp, and T. Asfour · 2016
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Y. Du, W. Wang, and L. Wang · 2015
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A. Jain, A. R. Zamir, S. Savarese, and A. Saxena · 2015
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NTU RGB+D: A large scale dataset for 3d human activity analysis
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Structured prediction of 3d human pose with deep neural networks
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Deep representation learning for human motion prediction and classification
J. Bütepage, M. J. Black, D. Kragic, and H. Kjellström · 2017
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