Search Results for "trip"

...Rather than requiring matching image pairs between source and target domains (which are often hard or impossible to obtain), CycleGAN learns two mappings — one from domain A to B, and another back from B to A — along with a cycle-consistency loss that encourages the round-trip to reconstruct the original image. This innovation lets the model learn domain-to-domain translations like turning horses into zebras, changing seasons, or transforming photos into paintings, using only collections of images from each domain. The original implementation (in Torch) has since been complemented by other re-implementations (including in PyTorch), but the core idea remains: unpaired image-to-image translation. ...