Unsupervised Zero-Shot Panoptic Segmentation
1 papers with code • 1 benchmarks • 0 datasets
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Unsupervised Universal Image Segmentation
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).