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Visual Grounding
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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?
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
A Neural Representation Framework with LLM-Driven Spatial Reasoning for Open-Vocabulary 3D Visual Grounding
VisualTrap: A Stealthy Backdoor Attack on GUI Agents via Visual Grounding Manipulation
GTA1: GUI Test-time Scaling Agent
High-Resolution Visual Reasoning via Multi-Turn Grounding-Based Reinforcement Learning
DenseWorld-1M: Towards Detailed Dense Grounded Caption in the Real World
SPAZER: Spatial-Semantic Progressive Reasoning Agent for Zero-shot 3D Visual Grounding
GroundFlow: A Plug-in Module for Temporal Reasoning on 3D Point Cloud Sequential Grounding
DrishtiKon: Multi-Granular Visual Grounding for Text-Rich Document Images
HalluSegBench: Counterfactual Visual Reasoning for Segmentation Hallucination Evaluation
GEMeX-ThinkVG: Towards Thinking with Visual Grounding in Medical VQA via Reinforcement Learning
Unified Representation Space for 3D Visual Grounding
I Speak and You Find: Robust 3D Visual Grounding with Noisy and Ambiguous Speech Inputs
Semantic Localization Guiding Segment Anything Model For Reference Remote Sensing Image Segmentation
Revisit What You See: Disclose Language Prior in Vision Tokens for Efficient Guided Decoding of LVLMs
EconWebArena: Benchmarking Autonomous Agents on Economic Tasks in Realistic Web Environments
Perceptual Decoupling for Scalable Multi-modal Reasoning via Reward-Optimized Captioning
From Objects to Anywhere: A Holistic Benchmark for Multi-level Visual Grounding in 3D Scenes
Does Your 3D Encoder Really Work? When Pretrain-SFT from 2D VLMs Meets 3D VLMs
RSVP: Reasoning Segmentation via Visual Prompting and Multi-modal Chain-of-Thought
GUI-Actor: Coordinate-Free Visual Grounding for GUI Agents
MoDA: Modulation Adapter for Fine-Grained Visual Grounding in Instructional MLLMs
D2AF: A Dual-Driven Annotation and Filtering Framework for Visual Grounding
mRAG: Elucidating the Design Space of Multi-modal Retrieval-Augmented Generation
Zero-Shot 3D Visual Grounding from Vision-Language Models
Mitigating Hallucination in Large Vision-Language Models via Adaptive Attention Calibration
Unveiling the Compositional Ability Gap in Vision-Language Reasoning Model
Two Causally Related Needles in a Video Haystack
Don't Look Only Once: Towards Multimodal Interactive Reasoning with Selective Visual Revisitation
OrionBench: A Benchmark for Chart and Human-Recognizable Object Detection in Infographics
CXReasonBench: A Benchmark for Evaluating Structured Diagnostic Reasoning in Chest X-rays
More Thinking, Less Seeing? Assessing Amplified Hallucination in Multimodal Reasoning Models
Training-Free Reasoning and Reflection in MLLMs
Redemption Score: An Evaluation Framework to Rank Image Captions While Redeeming Image Semantics and Language Pragmatics
Seeing the Trees for the Forest: Rethinking Weakly-Supervised Medical Visual Grounding
GUI-G1: Understanding R1-Zero-Like Training for Visual Grounding in GUI Agents
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.