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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 2632 of 32 papers

TitleStatusHype
Progressive Token Length Scaling in Transformer Encoders for Efficient Universal SegmentationCode0
COCONut: Modernizing COCO Segmentation0
SegICL: A Multimodal In-context Learning Framework for Enhanced Segmentation in Medical Imaging0
Towards Universal Vision-language Omni-supervised Segmentation0
Training a universal instance segmentation network for live cell images of various cell types and imaging modalitiesCode0
Universal Segmentation of 33 Anatomies0
Dynamic-structured Semantic Propagation Network0
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