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Composable Augmentation Encoding for Video Representation Learning (CATE)

This directory contains a colab to run inference with a pretrained CATE model. The model is used to extract self-supervised video representations, and we also provide demo code for nearest neighbor classification on the UCF-101 dataset.

For demo purposes we use the CATE model pretrained on the Kinetics-400 dataset. The checkpoints (exported with tfhub) for Something-Something v1 and v2 are also available in the same Google Cloud Storage directories.

For more information, please refer to our ICCV 2021 paper and project page.

If you use the code and the released checkpoints, please consider citing:

@InProceedings{Sun_CATE_CVPR2021,
author = {Chen Sun and Arsha Nagrani and Yonglong Tian and Cordelia Schmid},
title = {Composable Augmentation Encoding for Video Representation Learning},
booktitle = {ICCV},
year = {2021},
}