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Natural Language Visual Grounding
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Aguvis: Unified Pure Vision Agents for Autonomous GUI Interaction
ShowUI: One Vision-Language-Action Model for GUI Visual Agent
Improved GUI Grounding via Iterative Narrowing
OS-ATLAS: A Foundation Action Model for Generalist GUI Agents
Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agents
Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
OmniParser for Pure Vision Based GUI Agent
GUICourse: From General Vision Language Models to Versatile GUI Agents
Groma: Localized Visual Tokenization for Grounding Multimodal Large Language Models
SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents
CogAgent: A Visual Language Model for GUI Agents
MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning
Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
Localizing Moments in Long Video Via Multimodal Guidance
Visual Writing Prompts: Character-Grounded Story Generation with Curated Image Sequences
Belief Revision based Caption Re-ranker with Visual Semantic Information
TubeDETR: Spatio-Temporal Video Grounding with Transformers
CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks
Panoptic Narrative Grounding
Composing Pick-and-Place Tasks By Grounding Language
ALFWorld: Aligning Text and Embodied Environments for Interactive Learning
A Linguistic Analysis of Visually Grounded Dialogues Based on Spatial Expressions
Learning Cross-modal Context Graph for Visual Grounding
ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks
Searching for Ambiguous Objects in Videos using Relational Referring Expressions
Modularized Textual Grounding for Counterfactual Resilience
Self-Monitoring Navigation Agent via Auxiliary Progress Estimation
Robust Change Captioning
Learning to Assemble Neural Module Tree Networks for Visual Grounding
Grounding of Textual Phrases in Images by Reconstruction
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.