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Deep learning has enabled algorithms to generate realistic images.
Improved conditional vrnns for video prediction
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Deep predictive coding networks for video prediction and unsupervised learning
Time-agnostic prediction: Predicting predictable video frames
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Stochastic adversarial video prediction
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Approximate bayesian inference in spatial environments
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Unsupervised representation learning with deep convolutional generative adversarial networks
Radford, A., Metz, L., and Chintala, S · 2016
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Sønderby, C. K., Raiko, T., Maaløe, L., Sønderby, S. K., and Winther, O · 2016
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Stochastic variational video prediction
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Mujika, A., Meier, F., and Steger, A · 2017
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The unreasonable effectiveness of deep features as a perceptual metric
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Adversarial video generation on complex datasets
Clark, A., Donahue, J., and Simonyan, K · 2019
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Kim, T., Ahn, S., and Bengio, Y · 2019
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Very deep vaes generalize autoregressive models and can outperform them on images, 2020
Child, R · 2020
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Stochastic latent residual video prediction
Franceschi, J.-Y., Delasalles, E., Chen, M., Lamprier, S., and Gallinari, P · 2020
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Mastering atari with discrete world models
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Long-horizon visual planning with goal-conditioned hierarchical predictors
Pertsch, K., Rybkin, O., Ebert, F., Finn, C., Jayaraman, D., and Levine, S · 2020
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Nvae: A deep hierarchical variational autoencoder, 2020
Vahdat, A. and Kautz, J · 2020
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Scaling autoregressive video models
Weissenborn, D., Uszkoreit, J., and Täckström, O · 2020
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