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conv-lstm
keras-io/conv-lstm
conv-lstm is a video-to-video model from keras-io. Use it for the video-to-video task on the model card, and read the license before you ship it in a product. It is set up for tf-keras. The card lists the license as cc0-1.0.
This repo contains the models and the notebook on How to build and train a convolutional LSTM model for next-frame video prediction.
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At a glance
- Task
- Video-to-Video
- Library
- tf-keras
- License
- cc0-1.0
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- May 23, 2025
- SHA
- 7a530713
Spaces
Model card
From the Hugging Face model README
Tensorflow Keras Implementation of Next-Frame Video Prediction with Convolutional LSTMs 📽️
This repo contains the models and the notebook on How to build and train a convolutional LSTM model for next-frame video prediction.
Full credits to Amogh Joshi
Background Information
The Convolutional LSTM architectures bring together time series processing and computer vision by introducing a convolutional recurrent cell in a LSTM layer. This model uses the Convolutional LSTMs in an application to next-frame prediction, the process of predicting what video frames come next given a series of past frames.
Training Dataset
This model was trained on the Moving MNIST dataset.
For next-frame prediction, our model will be using a previous frame, which we'll call f_n, to predict a new frame, called f_(n + 1). To allow the model to create these predictions, we'll need to process the data such that we have "shifted" inputs and outputs, where the input data is frame x_n, being used to predict frame y_(n + 1).
- Task
- Video-to-Video
- Library
- tf-keras
- License
- cc0-1.0
- Created
- Mar 2, 2022
- Updated
- May 23, 2025