deit/README_patchconvnet.md

Augmenting Convolutional networks with attention-based aggregation

This repository contains PyTorch evaluation code, training code and pretrained models for the following projects:

• DeiT (Data-Efficient Image Transformers), ICML 2021
• CaiT (Going deeper with Image Transformers), ICCV 2021 (Oral)
• ResMLP (ResMLP: Feedforward networks for image classification with data-efficient training)
• PatchConvnet (Augmenting Convolutional networks with attention-based aggregation)

PatchConvnet provides interpretable attention maps to convnets:

For details see Augmenting Convolutional networks with attention-based aggregation by Hugo Touvron, Matthieu Cord, Alaaeldin El-Nouby, Matthieu Cord, Piotr Bojanowski, Armand Joulin, Gabriel Synnaeve and Hervé Jégou.

If you use this code for a paper please cite:

@article{touvron2021patchconvnet,
  title={Augmenting Convolutional networks with attention-based aggregation},
  author={Hugo Touvron and Matthieu Cord and Alaaeldin El-Nouby and Piotr Bojanowski and Armand Joulin and Gabriel Synnaeve and Jakob Verbeek and Herv'e J'egou},
  journal={arXiv preprint arXiv:2112.13692},
  year={2021},
}

Model Zoo

We provide PatchConvnet models pretrained on ImageNet-1k 2012:

name	acc@1	res	FLOPs	#params	url
S60	82.1	224	4.0B	25.2M	coming soon
S120	83.2	224	7.5B	47.7M	coming soon
B60	83.5	224	15.8B	99.4M	coming soon
B120	84.1	224	29.9B	188.6M	coming soon

Model pretrained on ImageNet-21k with finetuning on ImageNet-1k 2012:

name	acc@1	res	FLOPs	#params	url
S60	83.5	224	4.0B	25.2M	coming soon
S60	84.9	384	11.8B	25.2M	coming soon
S60	85.4	512	20.9B	25.2M	coming soon
B60	85.4	224	15.8B	99.4M	coming soon
B60	86.5	384	46.5B	99.4M	coming soon
B120	86.0	224	29.8B	188.6M	coming soon
B120	86.9	384	87.7B	188.6M	coming soon

The models are also available via torch hub. Before using it, make sure you have the latest pytorch-image-models package timm by Ross Wightman installed.

License

This repository is released under the Apache 2.0 license as found in the LICENSE file.

Contributing

We actively welcome your pull requests! Please see CONTRIBUTING.md and CODE_OF_CONDUCT.md for more info.