Comments (7)
I think you are right. Thank you for letting me know. I'll keep in mind this in my future works.
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Okay!And thanks for your great code work, this is a very clear template!
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Any intention to re-train all model in this repo? @plemeri
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I'm not planning to since this isn't our main contribution, but thanks for letting me know that the authors of CaraNet seems to be using our code without any citation. I really feel bad about it.
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Hello, yes i had sadly misunderstood the usage of the attention module for CaraNet. I initially thought, that they implemented the code similar, but ended up not using the axial attention, misinterpreting the inital gamma value of the self attention layer and mixing up the implementaton with the reverse attention module. It is indeed correct, that the axial attention is used by CaraNet, unreferenced in the published paper. However i think they reference that fact in the official repository.
I am sry for disturbing you with that comment and wanted to delete it, once i realized my initial assumption to be wrong.
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I just noticed that the author of CaraNet updated their readme.
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Related Issues (16)
- About SFA implementation HOT 3
- Results on ETIS-LaribPolypDB dataset HOT 3
- Clarification on pretrained weights HOT 1
- Could you please tell me how to get the CVC-300,CVC-ColonDB,ETIS dataset HOT 1
- A small question in Train.py
- About checkpoint saved HOT 1
- Why is my eval result 0 except for Sm, meanEm, mae, maxEm? HOT 2
- 关于 layers.py 中的一段代码
- The evaluation result is not good. HOT 11
- About this Baseline model HOT 4
- about "break" in train.py HOT 1
- about distributed training HOT 3
- Some questions about the ‘bce_iou_loss’ function HOT 2
- result problem HOT 1
- Multiple classes training HOT 2
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