https://github.com/moabitcoin/ig65m-pytorch

https://github.com/moabitcoin/ig65m-pytorch/releases

Hey folks, we ported the r(2+1)d video classification model (from CVPR 2018, see https://arxiv.org/abs/1711.11248) and the weights pre-trained by Facebook Research on over 65 million Instagram videos (from CVPR 2019, https://arxiv.org/abs/1905.00561) to PyTorch and released architecture, weights, tools for conversion, and feature extraction example.

The official Facebook Research codebase can be found at https://github.com/facebookresearch/vmz

These models and pre-trained weights are immensly powerful e.g. for fine-tuning on action recognition tasks or extracting features from 3d data such as videos. Think: resnet+imagenet but for videos.

We hope the PyTorch models and weights are useful for folks out there and are easier to use and work with compared to the goal driven, caffe2 based, research’y official code base.