Unofficial implementation of ViViT: A Video Vision Transformer.
- This is the implementation of model 2 only
- Can be initialized by the original Vit pretrained weight from Google: https://storage.googleapis.com/vit_models/imagenet21k/{model_name}.npz
- Support both "Filter inflation" and "Central frame" initialization for 3Dconv
- No number for Kinetic dataset since i don't have that kind of computational power
git clone https://github.com/NVIDIA/apex
cd apex
pip install -v --disable-pip-version-check --no-cache-dir ./
pip install -r requirements.txt
wget https://storage.googleapis.com/vit_models/imagenet21k/ViT-B_16.npz
python train_vivit.py --name test_cifar --pretrained_dir /ViT-B_16.npz --dataset cifar10@misc{arnab2021vivit,
title={ViViT: A Video Vision Transformer},
author={Anurag Arnab and Mostafa Dehghani and Georg Heigold and Chen Sun and Mario Lučić and Cordelia Schmid},
year={2021},
eprint={2103.15691},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
- Base ViT code and training setting are borrowed from @jeonsworld repo : https://github.com/jeonsworld/ViT-pytorch
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