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
1HyperSegOverall IoU83.4Unverified
2DeRIS-LOverall IoU82.87Unverified
3MLCD-Seg-7BOverall IoU81.5Unverified
4EVF-SAMOverall IoU80.2Unverified
5DETRISOverall IoU79Unverified
6C3VGOverall IoU77.86Unverified
7VATEXmIoU75.64Unverified
8MaskRIS (Swin-B, combined DB)Overall IoU75.1Unverified
9MaskRIS (Swin-B)Overall IoU73.96Unverified
10EVPOverall IoU72.94Unverified