UPSNet is a deep learning architecture for panoptic segmentation that combines semantic and instance segmentation into a single network. The model was introduced in a CVPR 2019 oral paper and is implemented in PyTorch, supporting multi-GPU training via horovod. It provides pretrained models and benchmarks on COCO and Cityscapes datasets, achieving competitive results on standard segmentation metrics.