GitHub - facebookresearch/SlowFast: Present SlowFast networks for video recognit...
source link: https://github.com/facebookresearch/SlowFast
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README.md
PySlowFast
PySlowFast is an open source video understanding codebase from FAIR that provides state-of-the-art video classification models, including papers "SlowFast Networks for Video Recognition", and "Non-local Neural Networks".
Introduction
The goal of PySlowFast is to provide a high-performance, light-weight pytorch codebase provides state-of-the-art video backbones for video understanding research. It is designed in order to support rapid implementation and evaluation of novel video research ideas. PySlowFast includes implementations of the following backbone network architectures:
- SlowFast
- SlowOnly
- C2D
- I3D
- Non-local Network
Updates
PySlowFast is released in conjunction with our ICCV 2019 Tutorial.
License
PySlowFast is released under the Apache 2.0 license.
Model Zoo and Baselines
We provide a large set of baseline results and trained models available for download in the PySlowFast Model Zoo.
Installation
Please find installation instructions for PyTorch and PySlowFast in INSTALL.md.
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