[R] Unsupervised Universal Image Segmentation

**Paper**: [https://arxiv.org/abs/2312.17243](https://arxiv.org/abs/2312.17243)

**Code**: [https://github.com/u2seg/U2Seg](https://github.com/u2seg/U2Seg)

**Project page**: [https://u2seg.github.io/](https://u2seg.github.io/)

**Abstract**:

>Several unsupervised image segmentation approaches have been proposed which eliminate the need for dense manually-annotated segmentation masks; current models separately handle either semantic segmentation (e.g., STEGO) or class-agnostic instance segmentation (e.g., CutLER), but not both (i.e., panoptic segmentation). We propose an Unsupervised Universal Segmentation model (**U2Seg**) adept at performing various image segmentation tasks -- instance, semantic and panoptic -- using a novel unified framework. U2Seg generates pseudo semantic labels for these segmentation …

abstract adept class current image instance machinelearning masks segmentation semantic tasks unsupervised