
CycleGAN: cycle-consistency is the key
How CycleGAN learns to translate between two image domains without a single matched pair — and why the cycle-consistency loss, not the adversarial loss, is what makes it work.
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How CycleGAN learns to translate between two image domains without a single matched pair — and why the cycle-consistency loss, not the adversarial loss, is what makes it work.