Open qibao77 opened 4 years ago
We use a combination of different losses to train our DSN, the loss between generated image and bicubicly downsampled image helps to maintain the content in the HR image. The adversarial loss helps the generated LR image capture the character of real-world LR images.
Thank you for your reply! I used the combination loss introduced in your paper, but my DSN became a "bicubic" down sampler. Can you give some advice?
For the design of DSN, how do you prevent DSN from completely becoming a "bicubic" down sampler, because when DSN is a "bicubic" down sampler, the loss will be very small.