Self-supervised Open-world Hierarchical Entity Segmentation with Improved Mask Quality

SOHES, a self-supervised approach, can segment entities and their constituent parts in an open-world setting without human annotations, achieving state-of-the-art performance and significantly closing the gap to supervised methods.