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We consider the problem of generating plausible and diverse video sequences, when we are only given a start and an end frame.
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Generative adversarial nets
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Dynamic Filter Networks
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Unsupervised Learning for Physical Interaction through Video Prediction
C. Finn, I. Goodfellow, and S. Levine · 2016
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning
W. Lotter, G. Kreiman, and D. Cox · 2016
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Deep multi-scale video prediction beyond mean square error
M. Mathieu, C. Couprie, and Y. LeCun · 2016
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A. Radford, L. Metz, and S. Chintala · 2016
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Temporal Generative Adversarial Nets with Singular Value Clipping
M. Saito, E. Matsumoto, and S. Saito · 2017
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MoCoGAN: Decomposing Motion and Content for Video Generation
S. Tulyakov, M.-Y. Liu, X. Yang, and J. Kautz · 2017
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Transformation-Based Models of Video Sequences
J. van Amersfoort, A. Kannan, M. Ranzato, A. Szlam, D. Tran, and S. Chintala · 2017
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FutureGAN: Anticipating the Future Frames of Video Sequences using Spatio-Temporal 3d Convolutions in Progressively Growing GANs
S. Aigner and M. Körner · 2018
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Stochastic Variational Video Prediction
M. Babaeizadeh, C. Finn, D. Erhan, R. H. Campbell, and S. Levine · 2018
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Stochastic Video Generation with a Learned Prior
E. Denton and R. Fergus · 2018
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Generating Videos with Scene Dynamics
C. Vondrick, H. Pirsiavash, and A. Torralba · 2016
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An Uncertain Future: Forecasting from Static Images using Variational Autoencoders
J. Walker, C. Doersch, A. Gupta, and M. Hebert · 2016
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Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks
T. Xue, J. Wu, K. L. Bouman, and W. T. Freeman · 2016
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Self-supervised visual planning with temporal skip connections
F. Ebert, C. Finn, A. Lee, and S. Levine · 2017
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GANs trained by a two time-scale update rule converge to a local nash equilibrium
M. Heusel, H. Ramsauer, T. Unterthiner, B. Nessler, and S. Hochreiter · 2017
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FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
E. Ilg, N. Mayer, T. Saikia, M. Keuper, A. Dosovitskiy, and T. Brox · 2017
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Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation
H. Jiang, D. Sun, V. Jampani, M.-H. Yang, E. Learned-Miller, and J. Kautz · 2018
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Video Generation and Synthesis Network for Long-term Video Interpolation
N. Kim, J. K. Lee, C. H. Yoo, S. Cho, and J.-w. Kang · 2018
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Stochastic Adversarial Video Prediction
A. X. Lee, R. Zhang, F. Ebert, P. Abbeel, C. Finn, and S. Levine · 2018
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PhaseNet for Video Frame Interpolation
S. Meyer, A. Djelouah, B. McWilliams, A. Sorkine-Hornung, M. Gross, and C. Schroers · 2018
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A Two-Stream Variational Adversarial Network for Video Generation
X. Sun, H. Xu, and K. Saenko · 2018
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Towards accurate generative models of video: A new metric & challenges
T. Unterthiner, S. van Steenkiste, K. Kurach, R. Marinier, M. Michalski, and S. Gelly · 2018
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Hierarchical Long-term Video Prediction without Supervision
N. Wichers, R. Villegas, D. Erhan, and H. Lee · 2018
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Stochastic Dynamics for Video Infilling
Q. Xu, H. Zhang, W. Wang, P. N. Belhumeur, and U. Neumann · 2018
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Style separation and synthesis via generative adversarial networks
R. Zhang, S. Tang, Y. Li, J. Guo, Y. Zhang, J. Li, and S. Yan · 2018
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