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Hi, I tried to change the L1 supervision to SSIM + L1 supervsion (0.85 * L_ssim + 0.15 L_l1), but failed to get good results. My motivation is that the original L1 supervision only focuses on a single pixel while discarding the local relationship of pixels, thus maybe better performance can be achieved by adding a structural loss like SSIM into supervision. I calculate the SSIM loss by sampling a batch of patches instead of pixels during training (since the memory consumption increases fast when the patch length is large, I only tried path length = 3, e.g. 9 pixels). I am wondering why the performance gets worse by adding the SSIM loss. Any discussion is welcome.
Thanks!
The text was updated successfully, but these errors were encountered:
Hi, I tried to change the L1 supervision to SSIM + L1 supervsion (0.85 * L_ssim + 0.15 L_l1), but failed to get good results. My motivation is that the original L1 supervision only focuses on a single pixel while discarding the local relationship of pixels, thus maybe better performance can be achieved by adding a structural loss like SSIM into supervision. I calculate the SSIM loss by sampling a batch of patches instead of pixels during training (since the memory consumption increases fast when the patch length is large, I only tried path length = 3, e.g. 9 pixels). I am wondering why the performance gets worse by adding the SSIM loss. Any discussion is welcome.
Thanks!
The text was updated successfully, but these errors were encountered: