Implementation of FitVid video prediction model in JAX/Flax.
If you find this code useful, please cite it in your paper:
@article{babaeizadeh2021fitvid,
title={FitVid: Overfitting in Pixel-Level Video Prediction},
author= {Babaeizadeh, Mohammad and Saffar, Mohammad Taghi and Nair, Suraj
and Levine, Sergey and Finn, Chelsea and Erhan, Dumitru},
journal={arXiv preprint arXiv:2106.13195},
year={2020}
}
FitVid is a new architecture for conditional variational video prediction. It has ~300 million parameters and can be trained with minimal training tricks.
Human3.6M | RoboNet |
---|---|
For more samples please visit FitVid. website: https://sites.google.com/view/fitvidpaper
Get dependencies:
pip3 install --user tensorflow
pip3 install --user tensorflow_addons
pip3 install --user flax
pip3 install --user ffmpeg
Train on RoboNet:
python -m fitvid.train --output_dir /tmp/output
Disclaimer: Not an official Google product.