CycleGAN is a generative adversarial network (GAN) architecture for unpaired image-to-image translation. It enables style transfer between two domains (e.g., photos to paintings, horses to zebras) without requiring paired training data. By using cycle consistency loss, CycleGAN ensures translated images remain consistent with the original content, making it popular in art generation, domain adaptation, and visual effects.
