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Hi, thanks for reading.
The 'main.py' in our codebase describes the setting of wider attribute dataset using VIT-CSRA models, say, step_size=5, lr_backbone=0.1, lr_fc=0.01. You can follow the same settings when using VIT-CSRA models in wider attribute dataset.
Hi, @sure7018, I'm not sure I fully understand your question.
You mean the improvement of the VIT structure, or the improvement of our VIT-CSRA model compared with orginal VIT model? In the later case, refer to the Table 3-4 in MS-COCO and wider-attribute datasets, which clearly demonstrate the performance gain of our method.
Hello, how to use CSRA in vit? There is no specific information in the paper?
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