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I tried to train a classification net using dcn (ResNet-50 with dcn in stage 5).
I view feature maps of the deformable conv layer and find that it cannot learn any useful things. Actually the content on each feature map is either 0 or a fixed constant.
I am wondering if there is a problem with the code or dcn is hard to train on the classification task. @unsky Do you have time to have a look at my classification network and maybe discuss this phenomenon with me?Thank you very much!
Here is my qq:819375556
The text was updated successfully, but these errors were encountered:
@unsky I also check out the offset that detection model(faster rcnn with ResNet50) learned. Its too small, like 1e-2~1e-3. It seems like the offset does not play any role...
@unsky I also check out the offset that detection model(faster rcnn with ResNet50) learned. Its too small, like 1e-2~1e-3. It seems like the offset does not play any role...
hello~ do you find the reason of the above-mentioned phenomenon?
I tried to train a classification net using dcn (ResNet-50 with dcn in stage 5).
I view feature maps of the deformable conv layer and find that it cannot learn any useful things. Actually the content on each feature map is either 0 or a fixed constant.
I am wondering if there is a problem with the code or dcn is hard to train on the classification task.
@unsky Do you have time to have a look at my classification network and maybe discuss this phenomenon with me?Thank you very much!
Here is my qq:819375556
The text was updated successfully, but these errors were encountered: