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作者您好! 我注意到代码中的Attention模块里面存在一个论文中未标注的shortcut被用于残差连接。 ![Z{C1PKZCY)U{I0KNMD@SF@A](https://github.com/Visual-Attention-Network/VAN-Classification/assets/57658728/f52a6a2c-4d6a-4e0d-96bb-39a5677a4518) ![H)O7HCK4{8R2ZY2O$6@HUCD](https://github.com/Visual-Attention-Network/VAN-Classification/assets/57658728/df8a4300-a0e4-4cde-9c44-aaec3bc8f500) 想请问一下,这个连接是必要的吗

![image](https://github.com/Visual-Attention-Network/VAN-Classification/assets/78601159/5db8fff2-2695-40db-8cc3-3998459f30a6) Is there a mistake here? The figure is 7x7, not 13x13?

Hi, thanks for your excellent code and paper.I am reproducing this paper using my own dataset, but I am getting this error.The pytorch version is the correct one. ![image](https://user-images.githubusercontent.com/104182010/181865979-7bcab7cd-d7b5-4194-a208-c1ff7e1cd3f2.png)

I read your paper and like it. but I have a one question. In this equation(3), there is (2d-1)^2 operations. It is depth-wise convolution so I think this may be...

In table 3, changing attention (mul) to add reduces VAN performance from 75.4 to 74.6. I think this is really huge. However, in the ablation study, you stated that "Besides,...

![image](https://user-images.githubusercontent.com/60497059/203268449-f6aff9b7-923c-49bd-92de-5f948d9221e5.png) Thank you so much for this enlightening and inspiring work.I don't quite understand why **LKC(i.e. Large Kernel Convolution) = DW-Conv + DW-D-Conv + 1x1Conv.** My current understanding can refer...

I found imagenet 22k pretrained models on [TsingHua Cloud](https://cloud.tsinghua.edu.cn/d/0100f0cea37d41ba8d08/). But I can't find 1k finetuned models. Do you have any release plans or links?