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An agent that is capable of predicting what happens next can perform a variety of tasks through planning with no additional training.
Few-shot video-to-video synthesis
Ting-Chun Wang, Ming-Yu Liu, Andrew Tao, Guilin Liu, Jan Kautz, and Bryan Catanzaro · 1910
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
Earlier work this paper cites.
Optimization of computer simulation models with rare events
Reuven Y Rubinstein · 1997
Earlier work this paper cites.
An introduction to variational methods for graphical models
Michael I Jordan, Zoubin Ghahramani, Tommi S Jaakkola, and Lawrence K Saul · 1999
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
Earlier work this paper cites.
Scope of validity of psnr in image/video quality assessment
Quan Huynh-Thu and Mohammed Ghanbari · 2008
Earlier work this paper cites.
Prediction, cognition and the brain
Andreja Bubic, D Yves Von Cramon, and Ricarda I Schubotz · 2010
Earlier work this paper cites.
Learning predictive models of a depth camera & manipulator from raw execution traces
Byron Boots, Arunkumar Byravan, and Dieter Fox · 2014
Earlier work this paper cites.
Nice: Non-linear independent components estimation
Laurent Dinh, David Krueger, and Yoshua Bengio · 2014
Earlier work this paper cites.
Generative adversarial networks
Ian J Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Human3. 6m: Large scale datasets and predictive methods for 3d human sensing in natural environments
Catalin Ionescu, Dragos Papava, Vlad Olaru, and Cristian Sminchisescu · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2014
Earlier work this paper cites.
Video (language) modeling: a baseline for generative models of natural videos
MarcAurelio Ranzato, Arthur Szlam, Joan Bruna, Michael Mathieu, Ronan Collobert, and Sumit Chopra · 2014
Earlier work this paper cites.
Stochastic backpropagation and approximate inference in deep generative models
Danilo Jimenez Rezende, Shakir Mohamed, and Daan Wierstra · 2014
Earlier work this paper cites.
Scheduled sampling for sequence prediction with recurrent neural networks
Samy Bengio, Oriol Vinyals, Navdeep Jaitly, and Noam Shazeer · 2015
Earlier work this paper cites.
A recurrent latent variable model for sequential data
Junyoung Chung, Kyle Kastner, Laurent Dinh, Kratarth Goel, Aaron Courville, and Yoshua Bengio · 2015
Earlier work this paper cites.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
Earlier work this paper cites.
Deep multi-scale video prediction beyond mean square error
Michael Mathieu, Camille Couprie, and Yann LeCun · 2015
Earlier work this paper cites.
Action-conditional video prediction using deep networks in atari games
Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard L Lewis, and Satinder Singh · 2015
Earlier work this paper cites.
Unsupervised learning of video representations using lstms
Nitish Srivastava, Elman Mansimov, and Ruslan Salakhudinov · 2015
Earlier work this paper cites.
Dense optical flow prediction from a static image
Jacob Walker, Abhinav Gupta, and Martial Hebert · 2015
Earlier work this paper cites.
Density estimation using real nvp
Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 2016
Earlier work this paper cites.
Deep spatial autoencoders for visuomotor learning
Chelsea Finn, Xin Yu Tan, Yan Duan, Trevor Darrell, Sergey Levine, and Pieter Abbeel · 2016
Earlier work this paper cites.
Nips 2016 tutorial: Generative adversarial networks
Ian Goodfellow · 2016
Earlier work this paper cites.
Deep learning , volume 1
Ian Goodfellow, Yoshua Bengio, Aaron Courville, and Yoshua Bengio · 2016
Earlier work this paper cites.
Gaussian error linear units (gelus)
Dan Hendrycks and Kevin Gimpel · 2016
Earlier work this paper cites.
Dynamic filter networks
Xu Jia, Bert De Brabandere, Tinne Tuytelaars, and Luc V Gool · 2016
Earlier work this paper cites.
Stochastic video prediction with conditional density estimation
Rui Shu, James Brofos, Frank Zhang, Hung Hai Bui, Mohammad Ghavamzadeh, and Mykel Kochenderfer · 2016
Earlier work this paper cites.
Generating videos with scene dynamics
Carl Vondrick, Hamed Pirsiavash, and Antonio Torralba · 2016
Earlier work this paper cites.
An uncertain future: Forecasting from static images using variational autoencoders
Jacob Walker, Carl Doersch, Abhinav Gupta, and Martial Hebert · 2016
Earlier work this paper cites.
Visual dynamics: Probabilistic future frame synthesis via cross convolutional networks
Tianfan Xue, Jiajun Wu, Katherine Bouman, and Bill Freeman · 2016
Earlier work this paper cites.
Se3-nets: Learning rigid body motion using deep neural networks
Arunkumar Byravan and Dieter Fox · 2017
Earlier work this paper cites.
Video imagination from a single image with transformation generation
Baoyang Chen, Wenmin Wang, and Jinzhuo Wang · 2017
Earlier work this paper cites.
Self-Supervised Visual Planning with Temporal Skip Connections
Frederik Ebert, Chelsea Finn, Alex X. Lee, and Sergey Levine · 2017
Earlier work this paper cites.
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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Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 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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Video frame synthesis using deep voxel flow
Ziwei Liu, Raymond A Yeh, Xiaoou Tang, Yiming Liu, and Aseem Agarwala · 2017
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Flexible spatio-temporal networks for video prediction
Chaochao Lu, Michael Hirsch, and Bernhard Scholkopf · 2017
Unsupervised learning of object structure and dynamics from videos
Matthias Minderer, Chen Sun, Ruben Villegas, Forrester Cole, Kevin Murphy, and Honglak Lee · 2019
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End-to-end time-lapse video synthesis from a single outdoor image
Seonghyeon Nam, Chongyang Ma, Menglei Chai, William Brendel, Ning Xu, and Seon Joo Kim · 2019
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Visual robot task planning
Chris Paxton, Yotam Barnoy, Kapil Katyal, Raman Arora, and Gregory D Hager · 2019
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High fidelity video prediction with large stochastic recurrent neural networks
Ruben Villegas, Arkanath Pathak, Harini Kannan, Dumitru Erhan, Quoc V Le, and Honglak Lee · 2019
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Scaling autoregressive video models
Dirk Weissenborn, Oscar Täckström, and Jakob Uszkoreit · 2019
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Searching for activation functions
Prajit Ramachandran, Barret Zoph, and Quoc V Le · 2017
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Parallel multiscale autoregressive density estimation
Scott E. Reed, Aäron van den Oord, Nal Kalchbrenner, Sergio Gomez Colmenarejo, Ziyu Wang, Yutian Chen, Dan Belov, and Nando de Freitas · 2017
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Transformation-based models of video sequences
Joost Van Amersfoort, Anitha Kannan, Marc’Aurelio Ranzato, Arthur Szlam, Du Tran, and Soumith Chintala · 2017
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Learning to generate long-term future via hierarchical prediction
Ruben Villegas, Jimei Yang, Yuliang Zou, Sungryull Sohn, Xunyu Lin, and Honglak Lee · 2017
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Generating the future with adversarial transformers
Carl Vondrick and Antonio Torralba · 2017
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Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A. Efros · 2017
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Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, et al · 2019
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Improvisation through physical understanding: Using novel objects as tools with visual foresight
Annie Xie, Frederik Ebert, Sergey Levine, and Chelsea Finn · 2019
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Solar: Deep structured representations for model-based reinforcement learning
Marvin Zhang, Sharad Vikram, Laura Smith, Pieter Abbeel, Matthew Johnson, and Sergey Levine · 2019
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Mohammad Babaeizadeh, Mohammad Taghi Saffar, Danijar Hafner, Harini Kannan, Chelsea Finn, Sergey Levine, and Dumitru Erhan · 2020
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Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
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Randaugment: Practical automated data augmentation with a reduced search space
Ekin D Cubuk, Barret Zoph, Jonathon Shlens, and Quoc V Le · 2020
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Video coding for machines: A paradigm of collaborative compression and intelligent analytics
Lingyu Duan, Jiaying Liu, Wenhan Yang, Tiejun Huang, and Wen Gao · 2020
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Stochastic latent residual video prediction
Jean-Yves Franceschi, Edouard Delasalles, Mickaël Chen, Sylvain Lamprier, and Patrick Gallinari · 2020
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Disentangling physical dynamics from unknown factors for unsupervised video prediction
Vincent Le Guen and Nicolas Thome · 2020
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Flax: A neural network library and ecosystem for JAX, 2020
Jonathan Heek, Anselm Levskaya, Avital Oliver, Marvin Ritter, Bertrand Rondepierre, Andreas Steiner, and Marc van Zee · 2020
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Learning to simulate dynamic environments with gamegan
Seung Wook Kim, Yuhao Zhou, Jonah Philion, Antonio Torralba, and Sanja Fidler · 2020
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Motion-aware feature enhancement network for video prediction
Xue Lin, Qi Zou, Xixia Xu, Yaping Huang, and Yi Tian · 2020
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Transformation-based adversarial video prediction on large-scale data
Pauline Luc, Aidan Clark, Sander Dieleman, Diego de Las Casas, Yotam Doron, Albin Cassirer, and Karen Simonyan · 2020
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Hierarchical foresight: Self-supervised learning of long-horizon tasks via visual subgoal generation
Suraj Nair and Chelsea Finn · 2020
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Trass: Time reversal as self-supervision
Suraj Nair, Mohammad Babaeizadeh, Chelsea Finn, Sergey Levine, and Vikash Kumar · 2020
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A review on deep learning techniques for video prediction
Sergiu Oprea, Pablo Martinez-Gonzalez, Alberto Garcia-Garcia, John Alejandro Castro-Vargas, Sergio Orts-Escolano, Jose Garcia-Rodriguez, and Antonis Argyros · 2020
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Offline reinforcement learning from images with latent space models
Rafael Rafailov, Tianhe Yu, Aravind Rajeswaran, and Chelsea Finn · 2020
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Ruslan Rakhimov, Denis Volkhonskiy, Alexey Artemov, Denis Zorin, and Evgeny Burnaev · 2020
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Nvae: A deep hierarchical variational autoencoder
Arash Vahdat and Jan Kautz · 2020
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Stochastic image-to-video synthesis using cinns
Michael Dorkenwald, Timo Milbich, Andreas Blattmann, Robin Rombach, Konstantinos G Derpanis, and Björn Ommer · 2021
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Drivegan: Towards a controllable high-quality neural simulation, 2021
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Revisiting hierarchical approach for persistent long-term video prediction
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Clockwork variational autoencoders for video prediction
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Can learned frame prediction compete with block motion compensation for video coding?
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Videogpt: Video generation using vq-vae and transformers
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