SOTAVerified

Referring Expression

Referring expressions places a bounding box around the instance corresponding to the provided description and image.

Papers

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Showing 51–75 of 364 papers

TitleStatusHype
Cross-Modal Bidirectional Interaction Model for Referring Remote Sensing Image SegmentationCode1
Grounding Language in Multi-Perspective Referential CommunicationCode0
Uni-Med: A Unified Medical Generalist Foundation Model For Multi-Task Learning Via Connector-MoECode1
FineCops-Ref: A new Dataset and Task for Fine-Grained Compositional Referring Expression ComprehensionCode1
MaPPER: Multimodal Prior-guided Parameter Efficient Tuning for Referring Expression ComprehensionCode1
Exploring Fine-Grained Image-Text Alignment for Referring Remote Sensing Image SegmentationCode1
LLM-wrapper: Black-Box Semantic-Aware Adaptation of Vision-Language Models for Referring Expression ComprehensionCode1
Referring Expression Generation in Visually Grounded Dialogue with Discourse-aware Comprehension GuidingCode0
Make Graph-based Referring Expression Comprehension Great Again through Expression-guided Dynamic Gating and Regression—0
SAM4MLLM: Enhance Multi-Modal Large Language Model for Referring Expression SegmentationCode2
A Lightweight Modular Framework for Low-Cost Open-Vocabulary Object Detection TrainingCode0
Revisiting Multi-Modal LLM Evaluation—0
3D-GRES: Generalized 3D Referring Expression SegmentationCode1
MaskInversion: Localized Embeddings via Optimization of Explainability Maps—0
Look Hear: Gaze Prediction for Speech-directed Human Attention—0
Learning Visual Grounding from Generative Vision and Language Model—0
Multi-branch Collaborative Learning Network for 3D Visual GroundingCode1
The Solution for the 5th GCAIAC Zero-shot Referring Expression Comprehension Challenge—0
SafaRi:Adaptive Sequence Transformer for Weakly Supervised Referring Expression Segmentation—0
Referring Atomic Video Action RecognitionCode1
M^2IST: Multi-Modal Interactive Side-Tuning for Efficient Referring Expression Comprehension—0
EVF-SAM: Early Vision-Language Fusion for Text-Prompted Segment Anything ModelCode3
Segment Anything Model for automated image data annotation: empirical studies using text prompts from Grounding DINO—0
ScanFormer: Referring Expression Comprehension by Iteratively Scanning—0
Revisiting Referring Expression Comprehension Evaluation in the Era of Large Multimodal ModelsCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RandomAcc@0.5m14.6—Unverified