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In the deep learning era, long video generation of high-quality still remains challenging due to the spatio-temporal complexity and continuity of videos.
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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Large-scale video classification with convolutional neural networks
Andrej Karpathy, George Toderici, Sanketh Shetty, Thomas Leung, Rahul Sukthankar, and Li Fei-Fei · 2014
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Wasserstein generative adversarial networks
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Unsupervised learning of disentangled representations from video
Emily Denton and Vighnesh Birodkar · 2017
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Terrance DeVries and Graham W Taylor · 2017
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GANs trained by a two time-scale update rule converge to a local nash equilibrium
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Nal Kalchbrenner, Aäron Oord, Karen Simonyan, Ivo Danihelka, Oriol Vinyals, Alex Graves, and Koray Kavukcuoglu · 2017
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The kinetics human action video dataset
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Temporal generative adversarial nets with singular value clipping
Masaki Saito, Eiichi Matsumoto, and Shunta Saito · 2017
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Aaron van den Oord, Oriol Vinyals, and Koray Kavukcuoglu · 2017
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Attention is all you need
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Ruben Villegas, Jimei Yang, Seunghoon Hong, Xunyu Lin, and Honglak Lee · 2017
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A short note about Kinetics-600
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Stochastic video generation with a learned prior
Emily Denton and Rob Fergus · 2018
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Deepfake video detection using recurrent neural networks
David Guera and Edward J. Delp · 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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Lars Mescheder, Andreas Geiger, and Sebastian Nowozin · 2018
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Vincent Sitzmann, Julien Martel, Alexander Bergman, David Lindell, and Gordon Wetzstein · 2020
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Fourier features let networks learn high frequency functions in low dimensional domains
Matthew Tancik, Pratul P Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T Barron, and Ren Ng · 2020
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CNN-generated images are surprisingly easy to spot… for now
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Scaling autoregressive video models
Dirk Weissenborn, Oscar Täckström, and Jakob Uszkoreit · 2020
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Differentiable augmentation for data-efficient GAN training
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Adversarial video generation on complex datasets
Aidan Clark, Jeff Donahue, and Karen Simonyan · 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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Image generators with conditionally-independent pixel synthesis
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FitVid: Overfitting in pixel-level video prediction
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Pi-GAN: Periodic implicit generative adversarial networks for 3D-aware image synthesis
Eric R Chan, Marco Monteiro, Petr Kellnhofer, Jiajun Wu, and Gordon Wetzstein · 2021
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Diffusion models beat GANs on image synthesis
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Latent neural differential equations for video generation
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Alias-free generative adversarial networks
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NeRF-VAE: A geometry aware 3D scene generative model
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Generative spoken language modeling from raw audio
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Revisiting hierarchical approach for persistent long-term video prediction
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Content-aware GAN compression
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NeRF in the wild: Neural radiance fields for unconstrained photo collections
Ricardo Martin-Brualla, Noha Radwan, Mehdi SM Sajjadi, Jonathan T Barron, Alexey Dosovitskiy, and Daniel Duckworth · 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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Deformable neural radiance fields
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Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
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A good image generator is what you need for high-resolution video synthesis
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Space-time neural irradiance fields for free-viewpoint video
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VideoGPT: Video generation using VQ-VAE and transformers
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