Unsupervised Zero-Shot Instance Segmentation
2 papers with code • 1 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Unsupervised Zero-Shot Instance Segmentation
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Libraries
Use these libraries to find Unsupervised Zero-Shot Instance Segmentation models and implementationsMost implemented papers
Cut and Learn for Unsupervised Object Detection and Instance Segmentation
facebookresearch/cutler
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CVPR 2023
We propose Cut-and-LEaRn (CutLER), a simple approach for training unsupervised object detection and segmentation models.
Unsupervised Universal Image Segmentation
u2seg/u2seg
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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).
