SOTAVerified

Visual Grounding

Visual Grounding (VG) aims to locate the most relevant object or region in an image, based on a natural language query. The query can be a phrase, a sentence, or even a multi-round dialogue. There are three main challenges in VG:

  • What is the main focus in a query?
  • How to understand an image?
  • How to locate an object?

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–250 of 571 papers

TitleStatusHype
Veagle: Advancements in Multimodal Representation LearningCode1
How Do Multimodal Large Language Models Handle Complex Multimodal Reasoning? Placing Them in An Extensible Escape GameCode1
Mask Grounding for Referring Image SegmentationCode1
Visual Grounding of Learned Physical ModelsCode1
EAGLE: Enhanced Visual Grounding Minimizes Hallucinations in Instructional Multimodal Models—0
Dynamic MDETR: A Dynamic Multimodal Transformer Decoder for Visual Grounding—0
Dynamic Inference With Grounding Based Vision and Language Models—0
LCV2: An Efficient Pretraining-Free Framework for Grounded Visual Question Answering—0
Bridging Modality Gap for Visual Grounding with Effecitve Cross-modal Distillation—0
A Neural Representation Framework with LLM-Driven Spatial Reasoning for Open-Vocabulary 3D Visual Grounding—0
ACTRESS: Active Retraining for Semi-supervised Visual Grounding—0
Language learning using Speech to Image retrieval—0
MNER-QG: An End-to-End MRC framework for Multimodal Named Entity Recognition with Query Grounding—0
MMR: Evaluating Reading Ability of Large Multimodal Models—0
BlenderAlchemy: Editing 3D Graphics with Vision-Language Models—0
MoDA: Modulation Adapter for Fine-Grained Visual Grounding in Instructional MLLMs—0
More Thinking, Less Seeing? Assessing Amplified Hallucination in Multimodal Reasoning Models—0
Data-Efficient 3D Visual Grounding via Order-Aware Referring—0
Don't Look Only Once: Towards Multimodal Interactive Reasoning with Selective Visual Revisitation—0
Mitigating Hallucination in Large Vision-Language Models via Adaptive Attention Calibration—0
I Speak and You Find: Robust 3D Visual Grounding with Noisy and Ambiguous Speech Inputs—0
INVIGORATE: Interactive Visual Grounding and Grasping in Clutter—0
Does Your 3D Encoder Really Work? When Pretrain-SFT from 2D VLMs Meets 3D VLMs—0
Beyond Object Categories: Multi-Attribute Reference Understanding for Visual Grounding—0
A Systematic Evaluation of GPT-4V's Multimodal Capability for Medical Image Analysis—0
3D Spatial Understanding in MLLMs: Disambiguation and Evaluation—0
Interpretable Visual Question Answering via Reasoning Supervision—0
Interpretable Visual Question Answering by Visual Grounding from Attention Supervision Mining—0
Interactive Visual Grounding of Referring Expressions for Human-Robot Interaction—0
Differentiable Parsing and Visual Grounding of Natural Language Instructions for Object Placement—0
Interactive Reinforcement Learning for Object Grounding via Self-Talking—0
Intent3D: 3D Object Detection in RGB-D Scans Based on Human Intention—0
Differentiable Disentanglement Filter: an Application Agnostic Core Concept Discovery Probe—0
Align2Ground: Weakly Supervised Phrase Grounding Guided by Image-Caption Alignment—0
Motion-Grounded Video Reasoning: Understanding and Perceiving Motion at Pixel Level—0
Joint Top-Down and Bottom-Up Frameworks for 3D Visual Grounding—0
Differentiable Disentanglement Filter: an Application Agnostic Core Concept Discovery Probe—0
Knowledge Supports Visual Language Grounding: A Case Study on Colour Terms—0
Benchmarking Diverse-Modal Entity Linking with Generative Models—0
AIFit: Automatic 3D Human-Interpretable Feedback Models for Fitness Training—0
Individuation in Neural Models with and without Visual Grounding—0
Language-Guided 3D Object Detection in Point Cloud for Autonomous Driving—0
Detecting Concrete Visual Tokens for Multimodal Machine Translation—0
Being data-driven is not enough: Revisiting interactive instruction giving as a challenge for NLG—0
LanguageRefer: Spatial-Language Model for 3D Visual Grounding—0
DSM: Building A Diverse Semantic Map for 3D Visual Grounding—0
Improving Visually Grounded Sentence Representations with Self-Attention—0
Dual Attribute-Spatial Relation Alignment for 3D Visual Grounding—0
DenseGrounding: Improving Dense Language-Vision Semantics for Ego-Centric 3D Visual Grounding—0
3DWG: 3D Weakly Supervised Visual Grounding via Category and Instance-Level Alignment—0
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All datasetsRefCOCO testARefCOCO+ test BRefCoCo val

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Florence-2-large-ftAccuracy (%)95.3—Unverified
2mPLUG-2Accuracy (%)92.8—Unverified
3X2-VLM (large)Accuracy (%)92.1—Unverified
4XFM (base)Accuracy (%)90.4—Unverified
5X2-VLM (base)Accuracy (%)90.3—Unverified
6X-VLM (base)Accuracy (%)89—Unverified
7HYDRAIoU61.7—Unverified
8HYDRAIoU61.1—Unverified
#ModelMetricClaimedVerifiedStatus
1Florence-2-large-ftAccuracy (%)92—Unverified
2mPLUG-2Accuracy (%)86.05—Unverified
3X2-VLM (large)Accuracy (%)81.8—Unverified
4XFM (base)Accuracy (%)79.8—Unverified
5X2-VLM (base)Accuracy (%)78.4—Unverified
6X-VLM (base)Accuracy (%)76.91—Unverified
#ModelMetricClaimedVerifiedStatus
1Florence-2-large-ftAccuracy (%)93.4—Unverified
2mPLUG-2Accuracy (%)90.33—Unverified
3X2-VLM (large)Accuracy (%)87.6—Unverified
4XFM (base)Accuracy (%)86.1—Unverified
5X2-VLM (base)Accuracy (%)85.2—Unverified
6X-VLM (base)Accuracy (%)84.51—Unverified