Mask2Former is a computer vision model using masked-attention transformers for universal image segmentation. It achieves state-of-the-art performance on panoptic, instance, and semantic segmentation tasks using a single unified architecture. The project supports major benchmarks including ADE20K, Cityscapes, COCO, and Mapillary Vistas, with trained models and a web demo available through Hugging Face Spaces.