The performance of CAM

[Zhengyang1995]

Hey, maybe this is question is not strongly related to this proj, but I will appreciate a lot if you could provide any advice for me.
The question is, do you have any idea about the miou performance for a classification network based on vgg (13 layers as backbone and with other 3 extra_conv).
When I try to reproduce your code ( The first step, train_cls.py), I remove the saliency and computing the background by a given threshold. I find that the miou drops. This is acceptable since saliency provides much useful information.
But when I try to remove other module in the vgg.py, to make it as a classification network, the best CAM I could get is among 42. You could find that in PSA, same backbone network(vgg16) could reach 48+.
At first, I wonder it is caused by the different parameters in the last three conv layers, but when I keep them as the same, I still can't reach 48.
Do you have any idea about the limitation? If so, I will appreciate a lot for your sincere help!