Closed howardgriffin closed 4 years ago
Hi, thanks for your attention.
The weights of the perceptual loss are taken from the previous work on reflection removal.
GAN plays as a regularization for our task and aims to fit the overall distribution. Thus, if we use a larger GAN loss, the output will not be produced as expected compared to the ground truth. and, we still want our network to mainly focus on pixel-wise restoration. The weight of GAN loss follows Pix2Pix and more details are discussed in that paper.
Hi, I am confused of the different weight of each vgg layer's perceptual loss , and the GAN loss weight seems to be very low compared with other loss. Could you make some explanation?