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In recent years, the task of video prediction-forecasting future video given past video frames-has attracted attention in the research community.
“Recognizing human actions: a local SVM approach”
Christian Schuldt, Ivan Laptev and Barbara Caputo · 2004
Earlier work this paper cites.
“Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.”
Yoshua Bengio, Nicholas Léonard and Aaron. Courville · 2013
Earlier work this paper cites.
“Video (language) modeling: a baseline for generative models of natural videos.”
Marc’Aurelio Ranzato, Arthur Szlam, Joan Bruna, Michaël Mathieu, Ronan Collobert and Sumit Chopra · 2014
Earlier work this paper cites.
“Action-Conditional Video Prediction using Deep Networks in Atari Games.”
Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard. Lewis and Satinder. Singh · 2015
Earlier work this paper cites.
“Spatio-temporal video autoencoder with differentiable memory”
Viorica Patraucean, Ankur Handa and Roberto Cipolla · 2015
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“Unsupervised Learning of Video Representations using LSTMs.”
Nitish Srivastava, Elman Mansimov and Ruslan Salakhutdinov · 2015
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“The New Data and New Challenges in Multimedia Research.”
Bart Thomee, David. Shamma, Gerald Friedland, Benjamin Elizalde, Karl Ni, Douglas Poland, Damian Borth and Li-Jia Li · 2015
Earlier work this paper cites.
“Unsupervised Learning for Physical Interaction through Video Prediction”
Chelsea Finn, Ian Goodfellow and Sergey Levine · 2016
Earlier work this paper cites.
“Dynamic Filter Networks.”
Xu Jia, Bert Brabandere, Tinne Tuytelaars and Luc Gool · 2016
Earlier work this paper cites.
“Deep multi-scale video prediction beyond mean square error.”
Michaël Mathieu, Camille Couprie and Yann LeCun · 2016
Earlier work this paper cites.
“Pixel Recurrent Neural Networks.”
Aäron van Oord, Nal Kalchbrenner and Koray Kavukcuoglu · 2016
Earlier work this paper cites.
“WaveNet: A Generative Model for Raw Audio”
Aaron Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew Senior and Koray Kavukcuoglu · 2016
Earlier work this paper cites.
“A note on the evaluation of generative models.”
Lucas Theis, Aäron van Oord and Matthias Bethge · 2016
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“Generating Videos with Scene Dynamics.”
Carl Vondrick, Hamed Pirsiavash and Antonio Torralba · 2016
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“An Uncertain Future: Forecasting from Static Images Using Variational Autoencoders.”
Jacob Walker, Carl Doersch, Abhinav Gupta and Martial Hebert · 2016
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“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.
“Self-Supervised Visual Planning with Temporal Skip Connections.”
Frederik Ebert, Chelsea Finn, Alex. Lee and Sergey Levine · 2017
Earlier work this paper cites.
“Progressive Growing of GANs for Improved Quality, Stability, and Variation”
Tero Karras, Timo Aila, Samuli Laine and Jaakko Lehtinen · 2017
Earlier work this paper cites.
“Predicting Deeper into the Future of Semantic Segmentation.”
Pauline Luc, Natalia Neverova, Camille Couprie, Jakob Verbeek and Yann LeCun · 2017
Earlier work this paper cites.
“The shape variational autoencoder: A deep generative model of part-segmented 3D objects.”
Charlie Nash and Christopher.. Williams · 2017
Earlier work this paper cites.
“Neural Discrete Representation Learning.”
Aäron van Oord, Oriol Vinyals and Koray Kavukcuoglu · 2017
Cited alongside, same era.
“Imagination-Augmented Agents for Deep Reinforcement Learning.”
Sébastien Racanière, Theophane Weber, David. Reichert, Lars Buesing, Arthur Guez, Danilo Rezende, Adriàènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter. Battaglia, Demis Hassabis, David Silver and Daan Wierstra · 2017
Cited alongside, same era.
“Parallel Multiscale Autoregressive Density Estimation.”
Scott. Reed, Aäron van Oord, Nal Kalchbrenner, Sergio Colmenarejo, Ziyu Wang, Yutian Chen, Dan Belov and Nando de Freitas · 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.
“Predicting Future Instance Segmentation by Forecasting Convolutional Features.”
Pauline Luc, Camille Couprie, Yann LeCun and Jakob Verbeek · 2018
Later among the works it cites.
“Folded Recurrent Neural Networks for Future Video Prediction.”
Marc Oliu, Javier Selva and Sergio Escalera · 2018
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“TGANv2: Efficient Training of Large Models for Video Generation with Multiple Subsampling Layers.”
Masaki Saito and Shunta Saito · 2018
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“MoCoGAN: Decomposing Motion and Content for Video Generation.”
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, Raphaël Marinier, Marcin Michalski and Sylvain Gelly · 2018
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“The Pose Knows: Video Forecasting by Generating Pose Futures.”
Jacob Walker, Kenneth Marino, Abhinav Gupta and Martial Hebert · 2017
Cited alongside, same era.
“MesoNet: a Compact Facial Video Forgery Detection Network”
D. Afchar, V. Nozick, J. Yamagishi and I. Echizen · 2018
Cited alongside, same era.
“Stochastic Variational Video Prediction”
Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy. Campbell and Sergey Levine · 2018
Cited alongside, same era.
“A Short Note about Kinetics-600.”
João Carreira, Eric Noland, Andras Banki-Horvath, Chloe Hillier and Andrew Zisserman · 2018
Cited alongside, same era.
“PixelSNAIL: An Improved Autoregressive Generative Model.”
Xi Chen, Nikhil Mishra, Mostafa Rohaninejad and Pieter Abbeel · 2018
Cited alongside, same era.
“Stochastic Video Generation with a Learned Prior”
Emily Denton and Rob Fergus · 2018
Cited alongside, same era.
“The challenge of realistic music generation: modelling raw audio at scale.”
Sander Dieleman, Aäron van Oord and Karen Simonyan · 2018
Cited alongside, same era.
“Learning to Generate Time-Lapse Videos Using Multi-Stage Dynamic Generative Adversarial Networks.”
Wei Xiong, Wenhan Luo, Lin Ma, Wei Liu and Jiebo Luo · 2018
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“Large Scale GAN Training for High Fidelity Natural Image Synthesis.”
Andrew Brock, Jeff Donahue and Karen Simonyan · 2019
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“Hierarchical Autoregressive Image Models with Auxiliary Decoders.”
Jeffrey Fauw, Sander Dieleman and Karen Simonyan · 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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“Generating High fidelity Images with subscale pixel Networks and Multidimensional Upscaling.”
Jacob Menick and Nal Kalchbrenner · 2019
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“Language models are unsupervised multitask learners”
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei and Ilya Sutskever · 2019
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“Generating Diverse High-Fidelity Images with VQ-VAE-2.”
Ali Razavi, Aäron van Oord and Oriol Vinyals · 2019
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“Recurrent Convolutional Strategies for Face Manipulation Detection in Videos”
Ekraam Sabir, Jiaxin Cheng, Ayush Jaiswal, Wael AbdAlmageed, Iacopo Masi and Prem Natarajan · 2019
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“On the Generalization of GAN Image Forensics”
Xinsheng Xuan, Bo Peng, Wei Wang and Jing Dong · 2019
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“Adversarial Video Generation on Complex Datasets”
Aidan Clark, Jeff Donahue and Karen Simonyan · 2020
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“Jukebox: A Generative Model for Music”
Prafulla Dhariwa, Heewoo Jun, Christine Payne, Jong Kim, Alec Radfor and Ilya Sutskever · 2020
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“VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation.”
Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh and Durk Kingma · 2020
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“Transformation-based Adversarial Video Prediction on Large-Scale Data.”
Pauline Luc, Aidan Clark, Sander Dieleman, Diego de Las, Yotam Doron, Albin Cassirer and Karen Simonyan · 2020
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“Scaling Autoregressive Video Models.”
Dirk Weissenborn, Oscar Täckström and Jakob Uszkoreit · 2020
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