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> The adversarial loss "learns" what is a compressed image and tries to make the decoder go away from such outputs. Could you expand on this point
by nbardy 6y ago
> The adversarial loss "learns" what is a compressed image and tries to make the decoder go away from such outputs.
Could you expand on this point
- atorodius 6y agoThe idea is that any distortion loss imposes specific artifacts. For example, MSE tends to blur outputs, CNN-feature-based losses (VGG, LPIPS) tend to produce gridding patterns or also blur. Now, when the discriminator network sees these artifacts, those artifacts very obviously distinguish the reconstructions from the input, and thus the gradients from the discriminator guide the optimization away from these artifacts. Let me know if this helps!