Closed yunseok624 closed 3 months ago
Hi, we originally were basing our code off of the Real-ESRGAN paper, which has slight differences from the original ESRGAN paper, one of which was using the standard GAN loss (in addition to Perceptual and L1). You could certainly try RaGAN if it's already implemented in BasicSR package.
Hi!
I see that in the paper you mentioned using ESGRAN with clip loss for optimal model for upscaling. In the original ESRGAN paper RaGAN (Relativistic average GAN) loss is used, however your code uses a standard GAN loss. Is there a special reason why you decided to use standard GAN loss?