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iccv citation + linear weights
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iccv citation + linear weights
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Mathilde Caron committed Aug 23, 2021
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Expand Up @@ -87,7 +87,7 @@ We also release XCiT models ([[`arXiv`](https://arxiv.org/abs/2106.09681)] [[`co
<th>params</th>
<th>k-nn</th>
<th>linear</th>
<th colspan="4">download</th>
<th colspan="5">download</th>
</tr>
<tr>
<td>xcit_small_12_p16</td>
Expand All @@ -98,6 +98,7 @@ We also release XCiT models ([[`arXiv`](https://arxiv.org/abs/2106.09681)] [[`co
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_small_12_p16_pretrain/dino_xcit_small_12_p16_pretrain_full_checkpoint.pth">full ckpt</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_small_12_p16_pretrain/args.txt">args</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_small_12_p16_pretrain/dino_xcit_small_12_p16_pretrain_log.txt">logs</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_small_12_p16_pretrain/dino_xcit_small_12_p16_pretrain_eval_linear_log.txt">eval</a></td>
</tr>
<tr>
<td>xcit_small_12_p8</td>
Expand All @@ -108,6 +109,7 @@ We also release XCiT models ([[`arXiv`](https://arxiv.org/abs/2106.09681)] [[`co
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_small_12_p8_pretrain/dino_xcit_small_12_p8_pretrain_full_checkpoint.pth">full ckpt</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_small_12_p8_pretrain/args.txt">args</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_small_12_p8_pretrain/dino_xcit_small_12_p8_pretrain_log.txt">logs</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_small_12_p8_pretrain/dino_xcit_small_12_p8_pretrain_eval_linear_log.txt">eval</a></td>
</tr>
<tr>
<td>xcit_medium_24_p16</td>
Expand All @@ -118,6 +120,7 @@ We also release XCiT models ([[`arXiv`](https://arxiv.org/abs/2106.09681)] [[`co
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_medium_24_p16_pretrain/dino_xcit_medium_24_p16_pretrain_full_checkpoint.pth">full ckpt</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_medium_24_p16_pretrain/args.txt">args</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_medium_24_p16_pretrain/dino_xcit_medium_24_p16_pretrain_log.txt">logs</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_medium_24_p16_pretrain/dino_xcit_medium_24_p16_pretrain_eval_linear_log.txt">eval</a></td>
</tr>
<tr>
<td>xcit_medium_24_p8</td>
Expand All @@ -128,6 +131,7 @@ We also release XCiT models ([[`arXiv`](https://arxiv.org/abs/2106.09681)] [[`co
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_medium_24_p8_pretrain/dino_xcit_medium_24_p8_pretrain_full_checkpoint.pth">full ckpt</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_medium_24_p8_pretrain/args.txt">args</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_medium_24_p8_pretrain/dino_xcit_medium_24_p8_pretrain_log.txt">logs</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_medium_24_p8_pretrain/dino_xcit_medium_24_p8_pretrain_eval_linear_log.txt">eval</a></td>
</tr>
</table>

Expand Down Expand Up @@ -257,6 +261,64 @@ To train a supervised linear classifier on frozen weights on a single node with
python -m torch.distributed.launch --nproc_per_node=8 eval_linear.py --data_path /path/to/imagenet
```

We release the logs and weights from evaluating the different models:

<table>
<tr>
<th>arch</th>
<th>top-1 ImageNet</th>
<th colspan="2">linear evaluation</th>
</tr>
<tr>
<td>ViT-S/16</td>
<td>77.0%</td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall16_pretrain/dino_deitsmall16_linearweights.pth">linear weights</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall16_pretrain/dino_deitsmall16_pretrain_eval_linear_log.txt">logs</a></td>
</tr>
<tr>
<td>ViT-S/8</td>
<td>79.7%</td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall8_pretrain/dino_deitsmall8_linearweights.pth">linear weights</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_deitsmall8_pretrain/dino_deitsmall8_pretrain_eval_linear_log.txt">logs</a></td>
</tr>
<tr>
<td>ViT-B/16</td>
<td>78.2%</td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_vitbase16_pretrain/dino_vitbase16_linearweights.pth">linear weights</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_vitbase16_pretrain/dino_vitbase16_pretrain_eval_linear_log.txt">logs</a></td>
</tr>
<tr>
<td>xcit_small_12_p16</td>
<td>77.8%</td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_small_12_p16_pretrain/dino_xcit_small_12_p16_linearweights.pth">linear weights</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_small_12_p16_pretrain/dino_xcit_small_12_p16_pretrain_eval_linear_log.txt">logs</a></td>
</tr>
<tr>
<td>xcit_small_12_p8</td>
<td>79.2%</td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_small_12_p8_pretrain/dino_xcit_small_12_p8_linearweights.pth">linear weights</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_small_12_p8_pretrain/dino_xcit_small_12_p8_pretrain_eval_linear_log.txt">logs</a></td>
</tr>
<tr>
<td>xcit_medium_24_p16</td>
<td>78.8%</td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_medium_24_p16_pretrain/dino_xcit_medium_24_p16_linearweights.pth">linear weights</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_medium_24_p16_pretrain/dino_xcit_medium_24_p16_pretrain_eval_linear_log.txt">logs</a></td>
</tr>
<tr>
<td>xcit_medium_24_p8</td>
<td>80.3%</td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_medium_24_p8_pretrain/dino_xcit_medium_24_p8_linearweights.pth">linear weights</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_xcit_medium_24_p8_pretrain/dino_xcit_medium_24_p8_pretrain_eval_linear_log.txt">logs</a></td>
</tr>
<tr>
<td>ResNet-50</td>
<td>75.3%</td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_resnet50_pretrain/dino_resnet50_linearweights.pth">linear weights</a></td>
<td><a href="https://dl.fbaipublicfiles.com/dino/dino_resnet50_pretrain/dino_resnet50_pretrain_eval_linear_log.txt">logs</a></td>
</tr>
</table>

## Evaluation: DAVIS 2017 Video object segmentation
Please verify that you're using pytorch version 1.7.1 since we are not able to reproduce the results with most recent pytorch 1.8.1 at the moment.

Expand Down Expand Up @@ -311,10 +373,10 @@ This repository is released under the Apache 2.0 license as found in the [LICENS
## Citation
If you find this repository useful, please consider giving a star :star: and citation :t-rex::
```
@article{caron2021emerging,
@inproceedings{caron2021emerging,
title={Emerging Properties in Self-Supervised Vision Transformers},
author={Caron, Mathilde and Touvron, Hugo and Misra, Ishan and J\'egou, Herv\'e and Mairal, Julien and Bojanowski, Piotr and Joulin, Armand},
journal={arXiv preprint arXiv:2104.14294},
booktitle={Proceedings of the International Conference on Computer Vision (ICCV)},
year={2021}
}
```

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