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--- |
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license: mit |
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--- |
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## CACR checkpoint repository |
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### For implementation details, please refer to our [Github Repo](https://github.com/JegZheng/CACR-SSL) |
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#### ImageNet pretrained, performance of linear classification on ImageNet |
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<table><tbody> |
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<!-- START TABLE --> |
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<!-- TABLE HEADER --> |
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<th align="left">model</th> |
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<th align="left">pretrain<br/>epochs</th> |
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<th align="left">linear<br/>acc</th> |
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<!-- TABLE BODY --> |
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<tr> |
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<td align="left">ResNet50</td> |
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<td align="left">1000</td> |
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<td align="left">74.7</td> |
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</tr> |
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<tr> |
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<td align="left">ViT-Base</td> |
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<td align="left">300</td> |
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<td align="left">77.1</td> |
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</tr> |
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</tbody></table> |
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#### ImageNet pretrained, performance of linear classification on 20 Image in the Wild datasets |
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Please feel free to check our learned representation performance in [Image in the Wild Challenge](https://eval.ai/web/challenges/challenge-page/1832/leaderboard/4301). |
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### Citation |
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Please cite our work if you find it is helpful. Thank you! |
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``` |
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@article{ |
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zheng2023contrastive, |
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title={Contrastive Attraction and Contrastive Repulsion for Representation Learning}, |
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author={Huangjie Zheng and Xu Chen and Jiangchao Yao and Hongxia Yang and Chunyuan Li and Ya Zhang and Hao Zhang and Ivor Tsang and Jingren Zhou and Mingyuan Zhou}, |
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journal={Transactions on Machine Learning Research}, |
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issn={2835-8856}, |
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year={2023}, |
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url={https://openreview.net/forum?id=f39UIDkwwc}, |
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} |
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``` |
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