Implementation of FitVid video prediction model in JAX/Flax.

Related tags

Deep Learning fitvid
Overview

FitVid Video Prediction Model

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}
}

Method

FitVid is a new architecture for conditional variational video prediction. It has ~300 million parameters and can be trained with minimal training tricks.

Architecture

Sample Videos

Human3.6M RoboNet
Humans1 RoboNet1
Humans2 RoboNet2

For more samples please visit FitVid. website: https://sites.google.com/view/fitvidpaper

Instructions

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.

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Comments
  • what tensorflow version?

    what tensorflow version?

    Hi, really interested in trying this out.

    I see that the augment file uses tensorflow.contrib which I assume means tensorflow 1.x. However when I set that and then run python -m fitvid.train.py --help it says it requires tensorflow 2.2 or greater

    opened by dvschultz 0
Owner
Google Research
Google Research
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