Hello,
I noticed that you use 15 as the weight for pixel loss, which is much larger than other weights such as for perceptual loss, frequency loss and also generator loss. If such a large coefficient is used, the influence of the discriminator will be reduced and the generator might become a direct estimator approximately. I would like to know if mode collapse can happen when the large weight for pixel loss is used.
BTW, I implemented conditional WGAN for MRI without pixel loss, but the image quality is not good enough.
Thanks!
Hello,
I noticed that you use 15 as the weight for pixel loss, which is much larger than other weights such as for perceptual loss, frequency loss and also generator loss. If such a large coefficient is used, the influence of the discriminator will be reduced and the generator might become a direct estimator approximately. I would like to know if mode collapse can happen when the large weight for pixel loss is used.
BTW, I implemented conditional WGAN for MRI without pixel loss, but the image quality is not good enough.
Thanks!