DINO_MNIST-PyTorch

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DINO_MNIST-PyTorch

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Pytorch implementation of "Emerging Properties in Self-Supervised Vision Transformers" (a.k.a. DINO)

DINO_MNIST-PyTorch 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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[PyTorch] DINO: self-DIstillation with NO labels
=====
PyTorch implementation of "Emerging Properties in Self-Supervised Vision Transformers"

## Concept
<div align="center">
  <img src="./figures/dino.png" width="400">    
  <p>Concept ot the DINO [1].</p>
</div>

## Results

### Summary
||Student ($x_1$)|Teacher ($x_2$)|
|:---|:---:|:---:|
|Before</br>(mismatch)|<img src="https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000000_s.png?raw=true" width="350">  |<img src="https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000000_t.png?raw=true" width="350">|  
|After</br>(matched)|<img src="https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000299_s.png?raw=true" width="350">  |<img src="https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000299_t.png?raw=true" width="350">|

### Detail (in Training)
|Epoch|Student ($x_1$)|Teacher ($x_2$)|
|:---|:---:|:---:|
|0|<img src="https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000000_s.png?raw=true" width="350">  |<img src="https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000000_t.png?raw=true" width="350">|  
|1|<img src="https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000001_s.png?raw=true" width="350">  |<img src="https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000001_t.png?raw=true" width="350">|  
|30|<img src="https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000030_s.png?raw=true" width="350">  |<img src="https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000030_t.png?raw=true" width="350">|  
|150|<img src="https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000150_s.png?raw=true" width="350">  |<img src="https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000150_t.png?raw=true" width="350">|  
|300|<img src="https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000299_s.png?raw=true" width="350">  |<img src="https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000299_t.png?raw=true" width="350">|

## Requirements
* PyTorch 2.0.1
* [MNIST.npz](https://github.com/lucastheis/deepbelief/blob/master/data/mnist.npz)

## Reference
[1] Mathilde Caron, et al. <a href="https://openaccess.thecvf.com/content/ICCV2021/html/Caron_Emerging_Properties_in_Self-Supervised_Vision_Transformers_ICCV_2021_paper.html">"Emerging Properties in Self-Supervised Vision Transformers."</a> Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021.

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