Comments

[victorca25]

Hello! Thanks for the great paper and code for AdaTarget, it is very interesting.

I've integrated in a model training framework here: https://github.com/victorca25/traiNNer/tree/master/codes/models/modules/adatarget , because I was interested in evaluating it simultaneously with other strategies and it appears to work pretty well when paired together with a complex augmentation pipeline, like the ones used in BSRGAN and Real-ESRGAN, as well as other network architectures besides ESRGAN.

From my tests I can also confirm:

• it works with AMP enabled, so training models can be done consuming less VRAM (at least)
• it can potentially also work with other cases besides SR
• it works well when paired with losses that work with unaligned images (not only GAN)

I'll have to do more and longer tests, but it's very promissing. I left the initial training of the localization network for later, since I didn't find a good way to integrate it for now.

If I find something that is useful, I can let you know. Cheers!

[yhjo09]

Hi, Thanks for your interest. I am glad to hear that it works well for your tasks as well. I believe such valuable information about practical experimental results will give an insight for researchers and practitioners. Please let us know if you find something in the next!