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
1MPG-SAM 2J&F73.9Unverified
2VRS-HQ (Chat-UniVi-13B)J&F71Unverified
3GLEE-ProJ&F70.6Unverified
4UNINEXT-HJ&F70.1Unverified
5ReferDINO (Swin-B)J&F69.3Unverified
6MUTRJ&F68.4Unverified
7VLP (VLMo-L)J&F67.6Unverified
8UniRef-L (Swin-L)J&F67.4Unverified
9DsHmp (Video-Swin-Base)J&F67.1Unverified
10HTR (Pre-training)J&F67.1Unverified