This repository provides a PyTorch implementation of unpaired image-to-image translation using patchwise contrastive learning combined with adversarial learning. The method avoids hand-crafted losses and inverse networks that CycleGAN uses, resulting in faster and more memory-efficient training. The approach can be extended to single-image training where each domain consists of only one image. Published at ECCV 2020.