4 citations · 10 across the 18 of their papers we have counts for
18 papers
CodeGraphVLP: Code-as-Planner Meets Semantic-Graph State for Non-Markovian Vision-Language-Action Models
Khoa Vo, Sieu Tran, Taisei Hanyu +8
Vision-Language-Action (VLA) models promise generalist robot manipulation, but are typically trained and deployed as short-horizon policies that assume the latest observation is su…
Clutter-Robust Vision-Language-Action Models through Object-Centric and Geometry Grounding
Khoa Vo, Taisei Hanyu, Yuki Ikebe +8
Recent Vision-Language-Action (VLA) models have made impressive progress toward general-purpose robotic manipulation by post-training large Vision-Language Models (VLMs) for action…
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…
EgoMusic-driven Human Dance Motion Estimation with Skeleton Mamba
Quang Nguyen, Nhat Le, Baoru Huang +6
Estimating human dance motion is a challenging task with various industrial applications. Recently, many efforts have focused on predicting human dance motion using either egocentr…
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…
RoboDesign1M: A Large-scale Dataset for Robot Design Understanding
Tri Le, Toan Nguyen, Quang Tran +6
Robot design is a complex and time-consuming process that requires specialized expertise. Gaining a deeper understanding of robot design data can enable various applications, inclu…
Towards Autonomous Wood-Log Grasping with a Forestry Crane: Simulator and Benchmarking
Minh Nhat Vu, Alexander Wachter, Gerald Ebmer +5
Forestry machines operated in forest production environments face challenges when performing manipulation tasks, especially regarding the complicated dynamics of underactuated cran…
Online Trajectory Replanner for Dynamically Grasping Irregular Objects
Minh Nhat Vu, Florian Grander, Anh Nguyen
This paper presents a new trajectory replanner for grasping irregular objects. Unlike conventional grasping tasks where the object's geometry is assumed simple, we aim to achieve a…
FedEFM: Federated Endovascular Foundation Model with Unseen Data
Tuong Do, Nghia Vu, Tudor Jianu +7
In endovascular surgery, the precise identification of catheters and guidewires in X-ray images is essential for reducing intervention risks. However, accurately segmenting cathete…
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…
GraspMamba: A Mamba-based Language-driven Grasp Detection Framework with Hierarchical Feature Learning
Huy Hoang Nguyen, An Vuong, Anh Nguyen +2
Grasp detection is a fundamental robotic task critical to the success of many industrial applications. However, current language-driven models for this task often struggle with clu…
CathAction: A Benchmark for Endovascular Intervention Understanding
Baoru Huang, Tuan Vo, Chayun Kongtongvattana +35
Real-time visual feedback from catheterization analysis is crucial for enhancing surgical safety and efficiency during endovascular interventions. However, existing datasets are of…
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…
Language-driven Grasp Detection
An Dinh Vuong, Minh Nhat Vu, Baoru Huang +4
Grasp detection is a persistent and intricate challenge with various industrial applications. Recently, many methods and datasets have been proposed to tackle the grasp detection p…
Autonomous Catheterization with Open-source Simulator and Expert Trajectory
Tudor Jianu, Baoru Huang, Tuan Vo +7
Endovascular robots have been actively developed in both academia and industry. However, progress toward autonomous catheterization is often hampered by the widespread use of close…
Language-driven Scene Synthesis using Multi-conditional Diffusion Model
An Vuong, Minh Nhat Vu, Toan Tien Nguyen +4
Scene synthesis is a challenging problem with several industrial applications. Recently, substantial efforts have been directed to synthesize the scene using human motions, room la…