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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 110 of 32 papers

TitleStatusHype
OMG-LLaVA: Bridging Image-level, Object-level, Pixel-level Reasoning and UnderstandingCode5
OneFormer: One Transformer to Rule Universal Image SegmentationCode3
Rethinking the Evaluation of Visible and Infrared Image FusionCode3
Hierarchical Open-vocabulary Universal Image SegmentationCode2
FOCUS: Towards Universal Foreground SegmentationCode2
HyperSeg: Hybrid Segmentation Assistant with Fine-grained Visual PerceiverCode2
InstructSeg: Unifying Instructed Visual Segmentation with Multi-modal Large Language ModelsCode2
HyperSeg: Towards Universal Visual Segmentation with Large Language ModelCode2
Large Language Model with Region-guided Referring and Grounding for CT Report GenerationCode2
Masked-attention Mask Transformer for Universal Image SegmentationCode2
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