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Videos show continuous events, yet most $-$ if not all $-$ video synthesis frameworks treat them discretely in time.
Sift flow: Dense correspondence across scenes and its applications
Ce Liu, Jenny Yuen, and Antonio Torralba · 2010
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Ucf101: A dataset of 101 human actions classes from videos in the wild
Khurram Soomro, Amir Roshan Zamir, and Mubarak Shah · 2012
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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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
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Patch to the future: Unsupervised visual prediction
Jacob Walker, Abhinav Gupta, and Martial Hebert · 2014
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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 representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2015
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Unsupervised learning of video representations using lstms
Nitish Srivastava, Elman Mansimov, and Ruslan Salakhudinov · 2015
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Learning spatiotemporal features with 3d convolutional networks
Du Tran, Lubomir Bourdev, Rob Fergus, Lorenzo Torresani, and Manohar Paluri · 2015
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Unsupervised learning for physical interaction through video prediction
Chelsea Finn, Ian Goodfellow, and Sergey Levine · 2016
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Generating videos with scene dynamics
Carl Vondrick, Hamed Pirsiavash, and Antonio Torralba · 2016
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Optimizing the latent space of generative networks
Piotr Bojanowski, Armand Joulin, David Lopez-Paz, and Arthur Szlam · 2017
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Quo vadis, action recognition? a new model and the kinetics dataset
Joao Carreira and Andrew Zisserman · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Video pixel networks
Nal Kalchbrenner, Aäron Oord, Karen Simonyan, Ivo Danihelka, Oriol Vinyals, Alex Graves, and Koray Kavukcuoglu · 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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Video frame interpolation via adaptive separable convolution
Simon Niklaus, Long Mai, and Feng Liu · 2017
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Temporal generative adversarial nets with singular value clipping
Masaki Saito, Eiichi Matsumoto, and Shunta Saito · 2017
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Towards high resolution video generation with progressive growing of sliced wasserstein gans
Dinesh Acharya, Zhiwu Huang, Danda Pani Paudel, and Luc Van Gool · 2018
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Large scale gan training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2018
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Super slomo: High quality estimation of multiple intermediate frames for video interpolation
Huaizu Jiang, Deqing Sun, Varun Jampani, Ming-Hsuan Yang, Erik Learned-Miller, and Jan Kautz · 2018
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Which training methods for gans do actually converge?
Lars Mescheder, Andreas Geiger, and Sebastian Nowozin · 2018
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cgans with projection discriminator
Takeru Miyato and Masanori Koyama · 2018
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Faceforensics: A large-scale video dataset for forgery detection in human faces
Andreas Rössler, Davide Cozzolino, Luisa Verdoliva, Christian Riess, Justus Thies, and Matthias Nießner · 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, Raphael Marinier, Marcin Michalski, and Sylvain Gelly · 2018
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Ting-Chun Wang, Ming-Yu Liu, Jun-Yan Zhu, Guilin Liu, Andrew Tao, Jan Kautz, and Bryan Catanzaro · 2018
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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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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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Image2stylegan: How to embed images into the stylegan latent space?
Rameen Abdal, Yipeng Qin, and Peter Wonka · 2019
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Depth-aware video frame interpolation
Wenbo Bao, Wei-Sheng Lai, Chao Ma, Xiaoyun Zhang, Zhiyong Gao, and Ming-Hsuan Yang · 2019
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Adversarial video generation on complex datasets
Aidan Clark, Jeff Donahue, and Karen Simonyan · 2019
Cited alongside, same era.
G3AN: Disentangling appearance and motion for video generation
Yaohui Wang, Piotr Bilinski, Francois Bremond, and Antitza Dantcheva · 2020
Later among the works it cites.
Scaling autoregressive video models
Dirk Weissenborn, Oscar Täckström, and Jakob Uszkoreit · 2020
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Image generators with conditionally-independent pixel synthesis
Ivan Anokhin, Kirill Demochkin, Taras Khakhulin, Gleb Sterkin, Victor Lempitsky, and Denis Korzhenkov · 2021
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Singan-gif: Learning a generative video model from a single gif
Rajat Arora and Yong Jae Lee · 2021
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Hierarchical video generation for complex data
Lluis Castrejon, Nicolas Ballas, and Aaron Courville · 2021
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pi-gan: Periodic implicit generative adversarial networks for 3d-aware image synthesis
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Kyle Genova, Forrester Cole, Daniel Vlasic, Aaron Sarna, William T Freeman, and Thomas Funkhouser · 2019
Cited alongside, same era.
A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
Cited alongside, same era.
Deep meta functionals for shape representation
Gidi Littwin and Lior Wolf · 2019
Cited alongside, same era.
Occupancy networks: Learning 3d reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
Cited alongside, same era.
Deepsdf: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
Cited alongside, same era.
First order motion model for image animation
Aliaksandr Siarohin, Stéphane Lathuilière, Sergey Tulyakov, Elisa Ricci, and Nicu Sebe · 2019
Cited alongside, same era.
Scene representation networks: Continuous 3d-structure-aware neural scene representations
Vincent Sitzmann, Michael Zollhöfer, and Gordon Wetzstein · 2019
Cited alongside, same era.
Eric R Chan, Marco Monteiro, Petr Kellnhofer, Jiajun Wu, and Gordon Wetzstein · 2021
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Nerv: Neural representations for videos
Hao Chen, Bo He, Hanyu Wang, Yixuan Ren, Ser-Nam Lim, and Abhinav Shrivastava · 2021
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Learning signal-agnostic implicit manifolds
Yilun Du, Katherine M. Collins, Joshua B. Tenenbaum, and Vincent Sitzmann · 2021
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Generative models as distributions of functions
Emilien Dupont, Yee Whye Teh, and Arnaud Doucet · 2021
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Stylevideogan: A temporal generative model using a pretrained stylegan
Gereon Fox, Ayush Tewari, Mohamed Elgharib, and Christian Theobalt · 2021
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Diverse generation from a single video made possible
Niv Haim, Ben Feinstein, Niv Granot, Assaf Shocher, Shai Bagon, Tali Dekel, and Michal Irani · 2021
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SAPE: Spatially-adaptive progressive encoding for neural optimization
Amir Hertz, Or Perel, Raja Giryes, Olga Sorkine-hornung, and Daniel Cohen-or · 2021
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Nerf-vae: A geometry aware 3d scene generative model
Adam R Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Soňa Mokrá, and Danilo J Rezende · 2021
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Neural scene flow fields for space-time view synthesis of dynamic scenes
Zhengqi Li, Simon Niklaus, Noah Snavely, and Oliver Wang · 2021
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Temporal shift gan for large scale video generation
Andres Munoz, Mohammadreza Zolfaghari, Max Argus, and Thomas Brox · 2021
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Vid-ode: Continuous-time video generation with neural ordinary differential equation
Sunghyun Park, Kangyeol Kim, Junsoo Lee, Jaegul Choo, Joonseok Lee, Sookyung Kim, and Edward Choi · 2021
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On buggy resizing libraries and surprising subtleties in fid calculation
Gaurav Parmar, Richard Zhang, and Jun-Yan Zhu · 2021
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Styleclip: Text-driven manipulation of stylegan imagery
Or Patashnik, Zongze Wu, Eli Shechtman, Daniel Cohen-Or, and Dani Lischinski · 2021
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D-nerf: Neural radiance fields for dynamic scenes
Albert Pumarola, Enric Corona, Gerard Pons-Moll, and Francesc Moreno-Noguer · 2021
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Adversarial generation of continuous images
Ivan Skorokhodov, Savva Ignatyev, and Mohamed Elhoseiny · 2021
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Aligning latent and image spaces to connect the unconnectable
Ivan Skorokhodov, Grigorii Sotnikov, and Mohamed Elhoseiny · 2021
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A good image generator is what you need for high-resolution video synthesis
Yu Tian, Jian Ren, Menglei Chai, Kyle Olszewski, Xi Peng, Dimitris N. Metaxas, and Sergey Tulyakov · 2021
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Jacob Walker, Ali Razavi, and Aäron van den Oord · 2021
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Inmodegan: Interpretable motion decomposition generative adversarial network for video generation
Yaohui Wang, Francois Bremond, and Antitza Dantcheva · 2021
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Space-time neural irradiance fields for free-viewpoint video
Wenqi Xian, Jia-Bin Huang, Johannes Kopf, and Changil Kim · 2021
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Videogpt: Video generation using vq-vae and transformers
Wilson Yan, Yunzhi Zhang, Pieter Abbeel, and Aravind Srinivas · 2021
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Generating videos with dynamics-aware implicit generative adversarial networks
Sihyun Yu, Jihoon Tack, Sangwoo Mo, Hyunsu Kim, Junho Kim, Jung-Woo Ha, and Jinwoo Shin · 2022
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