5 papers · 1 filter
GraspMAS: Zero-Shot Language-driven Grasp Detection with Multi-Agent System
Quang Nguyen, Tri Le, Huy Nguyen +5
Language-driven grasp detection has the potential to revolutionize human-robot interaction by allowing robots to understand and execute grasping tasks based on natural language com…
Robotic-CLIP: Fine-tuning CLIP on Action Data for Robotic Applications
Nghia Nguyen, Minh Nhat Vu, Tung D. Ta +4
Vision language models have played a key role in extracting meaningful features for various robotic applications. Among these, Contrastive Language-Image Pretraining (CLIP) is wide…
Language-driven Grasp Detection with Mask-guided Attention
Tuan Van Vo, Minh Nhat Vu, Baoru Huang +4
Grasp detection is an essential task in robotics with various industrial applications. However, traditional methods often struggle with occlusions and do not utilize language for g…
Lightweight Language-driven Grasp Detection using Conditional Consistency Model
Nghia Nguyen, Minh Nhat Vu, Baoru Huang +4
Language-driven grasp detection is a fundamental yet challenging task in robotics with various industrial applications. In this work, we present a new approach for language-driven…
Language-Driven 6-DoF Grasp Detection Using Negative Prompt Guidance
Toan Nguyen, Minh Nhat Vu, Baoru Huang +5
6-DoF grasp detection has been a fundamental and challenging problem in robotic vision. While previous works have focused on ensuring grasp stability, they often do not consider hu…