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Video prediction is a pixel-wise dense prediction task to infer future frames based on past frames.
Orientational selectivity of the human visual system
Fergus W Campbell and Janus J Kulikowski · 1966
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A theory for multiresolution signal decomposition: the wavelet representation
Stephane G Mallat · 1989
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Temporal properties of human visual filters: Number, shapes and spatial covariation
RF Hess and RJ Snowden · 1992
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Learning temporal transformations from time-lapse videos
Yipin Zhou and Tamara L Berg · 2002
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The effects of a visual fidelity criterion on the encoding of images
James Mannos and David Sakrison · 2003
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Recognizing human actions: a local svm approach
Christian Schuldt, Ivan Laptev, and Barbara Caputo · 2004
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
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A prediction- and cost function-based algorithm for robust autonomous freeway driving
Junqing Wei, John M Dolan, and Bakhtiar Litkouhi · 2010
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Pedestrian detection: An evaluation of the state of the art
Piotr Dollar, Christian Wojek, Bernt Schiele, and Pietro Perona · 2012
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Vision meets robotics: The kitti dataset
Andreas Geiger, Philip Lenz, Christoph Stiller, and Raquel Urtasun · 2013
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Stochastic backpropagation and approximate inference in deep generative models
Danilo Jimenez Rezende, Shakir Mohamed, and Daan Wierstra · 2014
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A recurrent latent variable model for sequential data
Junyoung Chung, Kyle Kastner, Laurent Dinh, Kratarth Goel, Aaron C Courville, and Yoshua Bengio · 2015
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Deep multi-scale video prediction beyond mean square error
Michael Mathieu, Camille Couprie, and Yann LeCun · 2015
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Unsupervised learning of video representations using lstms
Nitish Srivastava, Elman Mansimov, and Ruslan Salakhudinov · 2015
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Unsupervised detection and tracking of moving objects for video surveillance applications
Issam Elafi, Mohamed Jedra, and Noureddine Zahid · 2016
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High-speed all-optical haar wavelet transform for real-time image compression
Milad Alemohammad, Jasper R Stroud, Bryan T Bosworth, and Mark A Foster · 2017
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Stochastic variational video prediction
Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy H Campbell, and Sergey Levine · 2017
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Self-supervised visual planning with temporal skip connections
Frederik Ebert, Chelsea Finn, Alex X Lee, and Sergey Levine · 2017
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Deep visual foresight for planning robot motion
Chelsea Finn and Sergey Levine · 2017
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Wavelet-srnet: A wavelet-based cnn for multi-scale face super resolution
Huaibo Huang, Ran He, Zhenan Sun, and Tieniu Tan · 2017
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Dual motion gan for future-flow embedded video prediction
Xiaodan Liang, Lisa Lee, Wei Dai, and Eric P Xing · 2017
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Varnet: Exploring variations for unsupervised video prediction
Beibei Jin, Yu Hu, Yiming Zeng, Qiankun Tang, Shice Liu, and Jing Ye · 2018
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Stochastic adversarial video prediction
Alex X Lee, Richard Zhang, Frederik Ebert, Pieter Abbeel, Chelsea Finn, and Sergey Levine · 2018
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Dyan: A dynamical atoms-based network for video prediction
Wenqian Liu, Abhishek Sharma, Octavia Camps, and Mario Sznaier · 2018
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Folded recurrent neural networks for future video prediction
Marc Oliu, Javier Selva, and Sergio Escalera · 2018
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Sdc-net: Video prediction using spatially-displaced convolution
Fitsum A Reda, Guilin Liu, Kevin J Shih, Robert Kirby, Jon Barker, David Tarjan, Andrew Tao, and Bryan Catanzaro · 2018
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Ziwei Liu, Raymond A Yeh, Xiaoou Tang, Yiming Liu, and Aseem Agarwala · 2017
Cited alongside, same era.
Deep predictive coding networks for video prediction and unsupervised learning
William Lotter, Gabriel Kreiman, and David Cox · 2017
Cited alongside, same era.
Transformation-based models of video sequences
Joost Van Amersfoort, Anitha Kannan, Marc’Aurelio Ranzato, Arthur Szlam, Du Tran, and Soumith Chintala · 2017
Cited alongside, same era.
Decomposing motion and content for natural video sequence prediction
Ruben Villegas, Jimei Yang, Seunghoon Hong, Xunyu Lin, and Honglak Lee · 2017
Cited alongside, same era.
Learning to generate long-term future via hierarchical prediction
Ruben Villegas, Jimei Yang, Yuliang Zou, Sungryull Sohn, Xunyu Lin, and Honglak Lee · 2017
Cited alongside, same era.
Generating the future with adversarial transformers
C. Vondrick and A. Torralba · 2017
Cited alongside, same era.
Predrnn: Recurrent neural networks for predictive learning using spatiotemporal lstms
Yunbo Wang, Mingsheng Long, Jianmin Wang, Zhifeng Gao, and S Yu Philip · 2017
Cited alongside, same era.
Sergey Tulyakov, Ming-Yu Liu, Xiaodong Yang, and Jan Kautz · 2018
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Towards accurate generative models of video: A new metric & challenges
Thomas Unterthiner, Sjoerd van Steenkiste, Karol Kurach, Raphael Marinier, Marcin Michalski, and Sylvain Gelly · 2018
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Esrgan: Enhanced super-resolution generative adversarial networks
Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Yu Qiao, and Chen Change Loy · 2018
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Predrnn++: Towards a resolution of the deep-in-time dilemma in spatiotemporal predictive learning
Yunbo Wang, Zhifeng Gao, Mingsheng Long, Jianmin Wang, and Philip S Yu · 2018
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Novel video prediction for large-scale scene using optical flow
Henglai Wei, Xiaochuan Yin, and Penghong Lin · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Improved conditional vrnns for video prediction
Lluis Castrejon, Nicolas Ballas, and Aaron Courville · 2019
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Disentangling propagation and generation for video prediction
Hang Gao, Huazhe Xu, Qi-Zhi Cai, Ruth Wang, Fisher Yu, and Trevor Darrell · 2019
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Predicting future frames using retrospective cycle gan
Yong-Hoon Kwon and Min-Gyu Park · 2019
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Mutual suppression network for video prediction using disentangled features
Jungbeom Lee, Jangho Lee, Sungmin Lee, and Sungroh Yoon · 2019
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Eidetic 3d lstm: A model for video prediction and beyond
Yunbo Wang, Lu Jiang, Ming-Hsuan Yang, Li-Jia Li, Mingsheng Long, and Li Fei-Fei · 2019
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