Some questions for the papers about contrastivecrop HOT 4 CLOSED

The class score is the probability at the index of the gt class of that crop/image. It's not the argmax index. We use this score as an indicator of how much categorized semantic information the input crop contains.

from contrastivecrop.

Hi, Khoa-NT
Thank you for your interest and your questions.

1. Sorry for the confusion. By class score we mean the class probability after softmax (a real number within (0, 1)). We get the class score by inputting a crop to a standard ResNet50 trained with ImageNet labels. We didn't put it in the code since it is not the main experiment.
2. The linear classifier learning rate is adapted from MoCo. The linear cls lr is 30.0 in MoCo. We did a little parameter tuning to make it suitable for all models on small datasets.
3. It's a mistake that we did not remove the latter half sentence. Please ignore that.

from contrastivecrop.

Hi @xyupeng,
Thank you for your details and congratulation on the Oral paper.

In 1)

Sorry for the confusion. By class score we mean the class probability after softmax (a real number within (0, 1)). We get the class score by inputting a crop to a standard ResNet50 trained with ImageNet labels. We didn't put it in the code since it is not the main experiment.

If I understand correctly, the class score is the argmax class probability of the prediction (after softmax).
Did you check the predicted class, which is corresponding with that class probability, is the same as the GT?
I just wonder, if the predicted class was wrong, then maybe the semantic information is not useful.

from contrastivecrop.

Thank you for clarifying. I got it.

from contrastivecrop.