Can AutoAttack be used to dense prediction task?

[zhanglijun95]

Dear Author,

Thank you for your work and code! Recently I'm trying to apply AutoAttack on dense prediction tasks like semantic segmentation, but I got some error messages. So I'm wondering whether your package supports dense prediction task or currently it can only support classification task? Wait for your response. Thank you!

Best

[fra31]

Hi,

at the moment only classification tasks are supported. Adapting APGD and Square to optimize a different loss (i.e. when you have dense predictions) should be possible, but would require some adaptation of the code. If you have a reference to an example of the case you're considering, I'd be happy to have a look.

[zhanglijun95]

Thank you for your kind reply! The case I'm considering is a segmentation task. The input is in [B, C, H, W], where B is the batch size, C is 3, H and W are the height and width of the image. The label is in [B, 1, H, W], which indicates the class label for each pixel in the input. The output of the model is in [B, 40, H, W], where 40 is the number of classes for this segmentation task. Do you have any suggestion for me to fit my case? Thank you!