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Videos can often be created by first outlining a global description of the scene and then adding local details.
The neural autoregressive distribution estimator
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Diederik P Kingma and Max Welling · 2013
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Generative adversarial nets
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Nitish Srivastava, Elman Mansimov, and Ruslan Salakhudinov · 2015
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Rupesh Kumar Srivastava, Klaus Greff, and Jürgen Schmidhuber · 2015
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Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 2016
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Carl Vondrick, Hamed Pirsiavash, and Antonio Torralba · 2016
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Mohammad Babaeizadeh, Chelsea Finn, Dumitru Erhan, Roy H Campbell, and Sergey Levine · 2017
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Alex X Lee, Richard Zhang, Frederik Ebert, Pieter Abbeel, Chelsea Finn, and Sergey Levine · 2018
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Joao Carreira and Andrew Zisserman · 2017
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Parallel multiscale autoregressive density estimation
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Mocogan: Decomposing motion and content for video generation
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Bdd100k: A diverse driving video database with scalable annotation tooling
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Improved conditional vrnns for video prediction
Lluis Castrejon, Nicolas Ballas, and Aaron Courville · 2019
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Efficient video generation on complex datasets
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Language models are few-shot learners
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Scaling autoregressive video models
Dirk Weissenborn, Oscar Täckström, and Jakob Uszkoreit · 2020
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Towards image-to-video translation: A structure-aware approach via multi-stage generative adversarial networks
Long Zhao, Xi Peng, Yu Tian, Mubbasir Kapadia, and Dimitris N Metaxas · 2020
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