CycleGAN learns to translate images between domains (e.g., horses to zebras, photo to painting) without paired training data using adversarial networks and cycle-consistency losses. The repository includes CycleGAN, pix2pix, and related GAN-based translation methods originally published at ICCV 2017. It was implemented in Torch with a later PyTorch port.