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Universal Segmentation

Universal segmentation is a challenging computer vision task that aims to segment images into semantic regions, regardless of the task or the domain. It requires the model to learn a wide range of visual concepts and to be able to generalize to new tasks and domains.

Papers

Showing 26–32 of 32 papers

TitleStatusHype
Towards Universal Vision-language Omni-supervised Segmentation—0
Beyond Human Vision: The Role of Large Vision Language Models in Microscope Image Analysis—0
SegICL: A Multimodal In-context Learning Framework for Enhanced Segmentation in Medical Imaging—0
Dynamic-structured Semantic Propagation Network—0
Universal Segmentation of 33 Anatomies—0
COCONut: Modernizing COCO Segmentation—0
Towards Continual Universal Segmentation—0
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