Future Frame Prediction with Generative Adversarial Networks
Abstract: This report is about using generative adversarial networks with predictive coding networks for future frame prediction. Model selection choices for the components of the network are explored by training different models and testing their performance on next frame prediction in digital video from driving scenarios. Benefits and issues of using adversarial loss for future frame prediction as well as different choices for the model are discussed.
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