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DyHead PyTorch Implementation #10
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Hi Adam, Thanks a lot for your great work, it is really inspiring! However, I personally have some questions regarding scale-aware attention:
Please correct me if I did not understand it correctly. Again, thank you so much for your effort! Jerry |
Hi Jerry, I am not one of the authors of this paper, but I will try to answer them in the way I understood it. Just keep in mind that I might have things wrong, as what I said in my github repo.
Also thanks for your kind words. |
Hi Adam, Thanks for your quick response and detail explaination, it makes your thoughts more clear. Sorry that I didn't describe my question well at the first place. By "multi-sclae input", I actually meant raw input shape. Some detection frameworks like detectron2 support keep-ratio-resizeing with range of shortest edge value, like here. This can improve the robustness of the detection model, but it will cause the feature shape out from backbone to be arbitrary. So if we fix the s_size, we would probably fail on this scenario. |
Hi there,
Please look at my notes in my readme text file, hopefully, you can use this code to get a head start or to at least have the community have something to finish the implementation. If something, is incorrect in the code, I would really like to see the mistakes to see the things I misunderstood.
Thanks,
Adam