SOTAVerified

Referring Expression

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–250 of 364 papers

TitleStatusHype
Improving Referring Expression Grounding with Cross-modal Attention-guided Erasing—0
Improving the generation of personalised descriptions—0
Improving the Naturalness and Diversity of Referring Expression Generation models using Minimum Risk Training—0
Informativity in Image Captions vs. Referring Expressions—0
Instance-Aware Generalized Referring Expression Segmentation—0
Intrinsic Task-based Evaluation for Referring Expression Generation—0
Justifying Corpus-Based Choices in Referring Expression Generation—0
Key-Word-Aware Network for Referring Expression Image Segmentation—0
Language Controls More Than Top-Down Attention: Modulating Bottom-Up Visual Processing with Referring Expressions—0
Language-Guided 3D Object Detection in Point Cloud for Autonomous Driving—0
Language-Mediated, Object-Centric Representation Learning—0
Learning Distributions over Logical Forms for Referring Expression Generation—0
Learning Preferences for Referring Expression Generation: Effects of Domain, Language and Algorithm—0
Learning Pseudo-Labeler beyond Noun Concepts for Open-Vocabulary Object Detection—0
Learning to Generate Unambiguous Spatial Referring Expressions for Real-World Environments—0
Learning to Reason and Navigate: Parameter Efficient Action Planning with Large Language Models—0
Learning to Represent Image and Text with Denotation Graph—0
Learning Visual Grounding from Generative Vision and Language Model—0
Lessons from Computational Modelling of Reference Production in Mandarin and English—0
Leveraging Non-Specialists for Accurate and Time Efficient AMR Annotation—0
Leveraging Past References for Robust Language Grounding—0
LGD: Leveraging Generative Descriptions for Zero-Shot Referring Image Segmentation—0
Lite-MDETR: A Lightweight Multi-Modal Detector—0
Look Hear: Gaze Prediction for Speech-directed Human Attention—0
M^2IST: Multi-Modal Interactive Side-Tuning for Efficient Referring Expression Comprehension—0
MAGNet: Multi-Region Attention-Assisted Grounding of Natural Language Queries at Phrase Level—0
Make Graph-based Referring Expression Comprehension Great Again through Expression-guided Dynamic Gating and Regression—0
Mask-aware Text-to-Image Retrieval: Referring Expression Segmentation Meets Cross-modal Retrieval—0
MaskInversion: Localized Embeddings via Optimization of Explainability Maps—0
Meta Compositional Referring Expression Segmentation—0
Meteorologists and Students: A resource for language grounding of geographical descriptors—0
Modeling Semantic Expectation: Using Script Knowledge for Referent Prediction—0
Modular Graph Attention Network for Complex Visual Relational Reasoning—0
MuDoCo: Corpus for Multidomain Coreference Resolution and Referring Expression Generation—0
Multi-modal Domain Adaptation for REG via Relation Transfer—0
Referring Expression Generation in time-constrained communication—0
Referring Expression Generation under Uncertainty: Algorithm and Evaluation Framework—0
Joint Visual Grounding with Language Scene Graphs—0
Referring Expression Instance Retrieval and A Strong End-to-End Baseline—0
Referring Expressions with Rational Speech Act Framework: A Probabilistic Approach—0
Referring Image Segmentation by Generative Adversarial Learning—0
Referring Segmentation in Images and Videos with Cross-Modal Self-Attention Network—0
Referring to what you know and do not know: Making Referring Expression Generation Models Generalize To Unseen Entities—0
Refer to Anything with Vision-Language Prompts—0
RefTeacher: A Strong Baseline for Semi-Supervised Referring Expression Comprehension—0
REMI: Mining Intuitive Referring Expressions on Knowledge Bases—0
RESAnything: Attribute Prompting for Arbitrary Referring Segmentation—0
RESMatch: Referring Expression Segmentation in a Semi-Supervised Manner—0
Resolving Referring Expressions in Images With Labeled Elements—0
Revisiting Multi-Modal LLM Evaluation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RandomAcc@0.5m14.6—Unverified