SOTAVerified

Referring Expression Segmentation

The task aims at labeling the pixels of an image or video that represent an object instance referred by a linguistic expression. In particular, the referring expression (RE) must allow the identification of an individual object in a discourse or scene (the referent). REs unambiguously identify the target instance.

Papers

Showing 110 of 145 papers

TitleStatusHype
DeRIS: Decoupling Perception and Cognition for Enhanced Referring Image Segmentation through Loopback SynergyCode1
Mask-aware Text-to-Image Retrieval: Referring Expression Segmentation Meets Cross-modal Retrieval0
Refer to Anything with Vision-Language Prompts0
RemoteSAM: Towards Segment Anything for Earth ObservationCode3
VisionReasoner: Unified Visual Perception and Reasoning via Reinforcement LearningCode4
RESAnything: Attribute Prompting for Arbitrary Referring Segmentation0
3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation0
Towards Unified Referring Expression Segmentation Across Omni-Level Visual Target GranularitiesCode0
GroundingSuite: Measuring Complex Multi-Granular Pixel GroundingCode2
SegAgent: Exploring Pixel Understanding Capabilities in MLLMs by Imitating Human Annotator TrajectoriesCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeRIS-LMean IoU80.01Unverified
2MLCD-Seg-7BOverall IoU79.9Unverified
3HyperSegOverall IoU79.4Unverified
4UniLSeg-100Overall IoU79.27Unverified
5UniLSeg-20Overall IoU78.41Unverified
6EVF-SAMOverall IoU78.2Unverified
7SegAgentOverall IoU75.11Unverified
8DETRISOverall IoU74.6Unverified
9C3VGOverall IoU74.43Unverified
10GROUNDHOGOverall IoU74.1Unverified