activity
20222026
most citedLanguage-driven Scene Synthesis using Multi-conditional Diffusion Model

4 citations · 13 across the 24 of their papers we have counts for

collaborators

25 papers

cs.RO2026

Gripper-aware Vision Language Action Models

Hanyi Zhang, Zihong Luo, Tianyu Li +16

Vision language action models (VLAs) have advanced general purpose robotic grasping and manipulation by enabling robots to interpret visual observations and natural language instru…

cs.RO2026

Beyond Visual Grasping: Benchmarking Complex Grasping from Detection to Execution

Hanyi Zhang, Khang Nguyen, Charith Munasinghe +10

Robust robotic grasping remains a fundamental challenge for complex real-world applications. Recent advances in large-scale models demonstrate promising capabilities for reasoning…

cs.RO2026

MAGS-SLAM: Monocular Multi-Agent Gaussian Splatting SLAM for Geometrically and Photometrically Consistent Reconstruction

Zhihao Cao, Qi Shao, Shuhao Zhai +4

Collaborative photorealistic 3D reconstruction from multiple agents enables rapid large-scale scene capture for virtual production and cooperative multi-robot exploration. While re…

cs.RO2026

AeroScene: Progressive Scene Synthesis for Aerial Robotics

Nghia Vu, Tuong Do, Dzung Tran +6

Generative models have shown substantial impact across multiple domains, their potential for scene synthesis remains underexplored in robotics. This gap is more evident in drone si…

cs.CV2026

SIGMA: A Physics-Based Benchmark for Gas Chimney Understanding in Seismic Images

Bao Truong, Quang Nguyen, Baoru Huang +6

Seismic images reconstruct subsurface reflectivity from field recordings, guiding exploration and reservoir monitoring. Gas chimneys are vertical anomalies caused by subsurface flu…

cs.RO2025

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…

cs.RO2025

Humanoid Agent via Embodied Chain-of-Action Reasoning with Multimodal Foundation Models for Zero-Shot Loco-Manipulation

Congcong Wen, Geeta Chandra Raju Bethala, Yu Hao +8

Humanoid loco-manipulation, which integrates whole-body locomotion with dexterous manipulation, remains a fundamental challenge in robotics. Beyond whole-body coordination and bala…

cs.RO2025

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…

cs.RO2024

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…

cs.RO2024

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…

cs.RO2024★ 2 cited

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…

cs.RO2024

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…

cs.RO2024

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…

cs.RO2024★ 1 cited

Language-Driven Closed-Loop Grasping with Model-Predictive Trajectory Replanning

Huy Hoang Nguyen, Minh Nhat Vu, Florian Beck +3

Combining a vision module inside a closed-loop control system for a \emph{seamless movement} of a robot in a manipulation task is challenging due to the inconsistent update rates b…

cs.CV2024★ 2 cited

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…

cs.CV2024

High-fidelity Endoscopic Image Synthesis by Utilizing Depth-guided Neural Surfaces

Baoru Huang, Yida Wang, Anh Nguyen +3

In surgical oncology, screening colonoscopy plays a pivotal role in providing diagnostic assistance, such as biopsy, and facilitating surgical navigation, particularly in polyp det…

cs.RO2024★ 2 cited

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…

eess.IV2023

3D Guidewire Shape Reconstruction from Monoplane Fluoroscopic Images

Tudor Jianu, Baoru Huang, Pierre Berthet-Rayne +2

Endovascular navigation, essential for diagnosing and treating endovascular diseases, predominantly hinges on fluoroscopic images due to the constraints in sensory feedback. Curren…

eess.IV2023

Shape-Sensitive Loss for Catheter and Guidewire Segmentation

Chayun Kongtongvattana, Baoru Huang, Jingxuan Kang +3

We introduce a shape-sensitive loss function for catheter and guidewire segmentation and utilize it in a vision transformer network to establish a new state-of-the-art result on a…

cs.CV2023★ 4 cited

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…

cs.RO2023

Open-Vocabulary Affordance Detection using Knowledge Distillation and Text-Point Correlation

Tuan Van Vo, Minh Nhat Vu, Baoru Huang +4

Affordance detection presents intricate challenges and has a wide range of robotic applications. Previous works have faced limitations such as the complexities of 3D object shapes,…

cs.RO2023

Language-Conditioned Affordance-Pose Detection in 3D Point Clouds

Toan Nguyen, Minh Nhat Vu, Baoru Huang +6

Affordance detection and pose estimation are of great importance in many robotic applications. Their combination helps the robot gain an enhanced manipulation capability, in which…

cs.RO2023★ 2 cited

Grasp-Anything: Large-scale Grasp Dataset from Foundation Models

An Dinh Vuong, Minh Nhat Vu, Hieu Le +5

Foundation models such as ChatGPT have made significant strides in robotic tasks due to their universal representation of real-world domains. In this paper, we leverage foundation…

cs.CV2023

HabiCrowd: A High Performance Simulator for Crowd-Aware Visual Navigation

An Dinh Vuong, Toan Tien Nguyen, Minh Nhat VU +5

Visual navigation, a foundational aspect of Embodied AI (E-AI), has been significantly studied in the past few years. While many 3D simulators have been introduced to support visua…