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DINO: self-DIstillation with NO labels\n=====\nPyTorch implementation of \"Emerging Properties in Self-Supervised Vision Transformers\"\n\n## Concept\n\u003cdiv align=\"center\"\u003e\n  \u003cimg src=\"./figures/dino.png\" width=\"400\"\u003e    \n  \u003cp\u003eConcept ot the DINO [1].\u003c/p\u003e\n\u003c/div\u003e\n\n## Results\n\n### Summary\n||Student ($x_1$)|Teacher ($x_2$)|\n|:---|:---:|:---:|\n|Before\u003c/br\u003e(mismatch)|\u003cimg src=\"https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000000_s.png?raw=true\" width=\"350\"\u003e  |\u003cimg src=\"https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000000_t.png?raw=true\" width=\"350\"\u003e|  \n|After\u003c/br\u003e(matched)|\u003cimg src=\"https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000299_s.png?raw=true\" width=\"350\"\u003e  |\u003cimg src=\"https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000299_t.png?raw=true\" width=\"350\"\u003e|  \n\n### Detail (in Training)\n|Epoch|Student ($x_1$)|Teacher ($x_2$)|\n|:---|:---:|:---:|\n|0|\u003cimg src=\"https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000000_s.png?raw=true\" width=\"350\"\u003e  |\u003cimg src=\"https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000000_t.png?raw=true\" width=\"350\"\u003e|  \n|1|\u003cimg src=\"https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000001_s.png?raw=true\" width=\"350\"\u003e  |\u003cimg src=\"https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000001_t.png?raw=true\" width=\"350\"\u003e|  \n|30|\u003cimg src=\"https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000030_s.png?raw=true\" width=\"350\"\u003e  |\u003cimg src=\"https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000030_t.png?raw=true\" width=\"350\"\u003e|  \n|150|\u003cimg src=\"https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000150_s.png?raw=true\" width=\"350\"\u003e  |\u003cimg src=\"https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000150_t.png?raw=true\" width=\"350\"\u003e|  \n|300|\u003cimg src=\"https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000299_s.png?raw=true\" width=\"350\"\u003e  |\u003cimg src=\"https://github.com/YeongHyeon/DINO_MNIST-PyTorch/blob/main/figures/epoch_000299_t.png?raw=true\" width=\"350\"\u003e|  \n\n## Requirements\n* PyTorch 2.0.1\n\n## Reference\n[1] Mathilde Caron, et al. \u003ca href=\"https://openaccess.thecvf.com/content/ICCV2021/html/Caron_Emerging_Properties_in_Self-Supervised_Vision_Transformers_ICCV_2021_paper.html\"\u003e\"Emerging Properties in Self-Supervised Vision Transformers.\"\u003c/a\u003e Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyeonghyeon%2Fdino_mnist-pytorch","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fyeonghyeon%2Fdino_mnist-pytorch","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyeonghyeon%2Fdino_mnist-pytorch/lists"}