5 papers
Learning Human Motion with Temporally Conditional Mamba
Quang Nguyen, Tri Le, Baoru Huang +4
Learning human motion based on a time-dependent input signal presents a challenging yet impactful task with various applications. The goal of this task is to generate or estimate h…
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…