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# Augmenting Convolutional networks with attention-based aggregation
This repository contains PyTorch evaluation code, training code and pretrained models for the following projects:
* [DeiT](README.md) (Data-Efficient Image Transformers), ICML 2021
* [CaiT](README_cait.md) (Going deeper with Image Transformers), ICCV 2021 (Oral)
* [ResMLP](README_resmlp.md) (ResMLP: Feedforward networks for image classification with data-efficient training)
* PatchConvnet (Augmenting Convolutional networks with attention-based aggregation)
PatchConvnet allows to have interpretable attention maps with convnets:
<p align="center">
<img width="900" src=".github/patch_convnet.png">
</p>
For details see [Augmenting Convolutional networks with attention-based aggregation](https://arxiv.org/abs/2112.13692) 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`](https://github.com/rwightman/pytorch-image-models) by [Ross Wightman](https://github.com/rwightman) installed.
# License
This repository is released under the Apache 2.0 license as found in the [LICENSE](LICENSE) file.
# Contributing
We actively welcome your pull requests! Please see [CONTRIBUTING.md](.github/CONTRIBUTING.md) and [CODE_OF_CONDUCT.md](.github/CODE_OF_CONDUCT.md) for more info.