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Pytorch implementations of ConvLSTM and ConvGRU modules with examples
In this repository, we focus on video frame prediction the task of predicting future frames given a set of past frames. We present an Adversarial Spatio-Temporal Convolutional LSTM architecture to predict the future frames of the Moving MNIST Dataset. We evaluate the model on long-term future frame prediction and its performance of the model on out-of-domain inputs by providing sequences on which the model was not trained.
Implementation of Convolutional Encoder Decoder Network for short term (0 - 2 hours) weather forecasting.
Pytorch Implementation of the Paper: Self-Attention ConvLSTM for Spatiotemporal Prediction
Next-Frame Prediction Using Convolutional LSTM