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I want to know, are you pretraining the teacher on ImageNet ?
In the paper, they mentioned that Teacher is pretrained on ImageNet. Is your repo following it ?
The text was updated successfully, but these errors were encountered:
Yes, that i am clear. As you have provided, ResNet weights for classes separately, I am sure you are training the pretrained ResNet on that Class, ex Carpet. Am i right ?
Just one more important thing is, were you able to reproduce the AUROC results of paper by your method ? Because I am getting lesser AUROC than mentioned in paper.
Yes you are right 👍
Concerning the ROC, the paper is actually not computing the ROC to evaluate their models, instead they compute the PRO (per region overlap). I simply decided to use the ROC for simplicity but implementing the PRO could be a nice exercise !
I want to know, are you pretraining the teacher on ImageNet ?
In the paper, they mentioned that Teacher is pretrained on ImageNet. Is your repo following it ?
The text was updated successfully, but these errors were encountered: