Went through the paper. Yeah, they seem to propose vgg loss as an alternative to mse loss. Since mse is directly related to psnr, it would be ideal to train it with mse. But in this case, since we are worried more about the perceptual quality they are using vgg perceptual loss. So, that’s the reason they have used mean opinion score measures. Now, coming to making it work, it will be better to have a smaller patch (96x96) as mentioned in the paper. Train for higher number of epochs compared to the one you do with mse, because there is no direct correlation.  I have also seen similar works which tries to bring in a indirect relation to pixel-level mapping, but i had hard time making it work.