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We consider the problem of next frame prediction from video input.
Long short-temp memory
S. Hochreiter and J. Schmidhuber · 1997
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A system for traffic sign detection, tracking, and recognition using color, shape, and motion information
C. Bahlmann, Y. Zhu, V. Ramesh, M. Pellkofer, and T. Koehler · 2005
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Image quality metrics: Psnr vs. ssim
A. Hore and D. Ziou · 2010
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Road scene segmentation from a single image
J. Alvarez, T. Gevers, Y. LeCun, and A. Lopez · 2012
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A system for real-time detection and tracking of vehicles from a single car-mounted camera
C. Caraffi, T. Vojir, J. Trefny, J. Sochman, and J. Matas · 2012
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Pedestrian detection: An evaluation of the state of the art
P. Dollar, C. Wojek, B. Schiele, and P. Perona · 2012
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Variational recursive joint estimation of dense scene structure and camera motion from monocular high speed traffic sequences
F. Becker, F. Lenzen, J. H. Kappes, and C. Schnorr · 2013
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Knn matting
Q. Chen, D. Hong, and C. Tang · 2013
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Vision meets robotics: The kitti dataset
A. Geiger, P. Lenz, C. Stiller, and R. Urtasun · 2013
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Ten years of pedestrian detection, what have we learned?
R. Benenson, M. Omran, J. Hosang, and B. Schiele · 2014
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3d traffic scene understanding from movable platforms
A. Geiger, M. Lauer, C. Wojek, C. Stiller, and R. Urtasun · 2014
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Adam: A method for stochastic optimization
D. Kingma and J. Ba · 2014
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Modeling deep temporal dependencies with recurrent grammar cells
V. Michalski, R. Memisevic, and K. Konda · 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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Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture
D. Eigen and R. Fergus · 2015
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Towards unified depth and semantic prediction from a single image
P. Wang et al · 2015
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Convolutional lstm network: A machine learning approach for precipitation nowcasting
X. Shi et al · 2015
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Single-image depth perception in the wild
W. Chen, Z. Fu, D. Yang, and J. Deng · 2016
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Map-based long term motion prediction for vehicles in traffic environments
D. Petrich et al · 2016
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Tensorflow: A system for large-scale machine learning
M. Abadi et al · 2016
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Unsupervised learning for physical interaction through video prediction
C. Finn, I. Goodfellow, and S. Levine · 2016
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Learning predictive visual models of physics for playing billiards
K. Fragkiadaki, P. Agrawal, S. Levine, and J. Malik · 2016
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Unsupervised cnn for single view depth estimation: Geometry to the rescue
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P. Fischer, A. Dosovitskiy, E. Ilg, P. Häusser, C. Hazırbaş, V. Golkov, P. van der Smagt, D. Cremers, and T. Brox · 2015
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Deep multi-scale video prediction beyond mean square error
M. Mathieu, C. Couprie, and Y. LeCun · 2015
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Action-conditional video prediction using deep networks in atari games
J. Oh, X. Guo, H. Lee, R. L Lewis, and S. Singh · 2015
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Unsupervised learning of video representations using lstms
N. Srivastava, E. Mansimov, and R. Salakhutdinov · 2015
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Dense optical flow prediction from a static image
J. Walker, A. Gupta, and M. Hebert · 2015
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J. Ba, J. Kiros, and G. Hinton · 2016
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R. Garg, V. Kumar, G. Carneiro, and I. Reid · 2016
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Deeper depth prediction with fully convolutional residual networks
I. Laina, C. Rupprecht, V. Belagiannis, F. Tombari, and N. Navab · 2016
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Monocular 3d shape reconstruction using deep neural networks
Q. Rao, L. Krüger, and K.Dietmayer · 2016
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Semantic stixels: Depth is not enough
L. Schneider, M. Cordts, T. Rehfeld, D. Pfeiffer, M. Enzweiler, U. Franke, M. Pollefeys, and S. Roth · 2016
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Anticipating visual representations from unlabeled video
C. Vondrick, H. Pirsiavash, and A. Torralba · 2016
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Probabilistic modeling of future frames from a single image
T. Xue, J. Wu, K. Bouman, and Freeman W · 2016
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