This repository provides a PyTorch implementation of an adversarial domain adaptation method for semantic segmentation. The approach adapts a segmentation model trained on synthetic (source domain) data to real-world (target domain) images using adversarial learning in the output space. Based on this method, the authors achieved 3rd place in the VisDA 2017 Challenge. The implementation includes training scripts, evaluation tools, and support for LS-GAN objectives.