4 citations · 12 across the 15 of their papers we have counts for
16 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…
More Reliable Pseudo-labels, Better Performance: A Generalized Approach to Single Positive Multi-label Learning
Luong Tran, Thieu Vo, Anh Nguyen +2
Multi-label learning is a challenging computer vision task that requires assigning multiple categories to each image. However, fully annotating large-scale datasets is often imprac…
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…
OZSpeech: One-step Zero-shot Speech Synthesis with Learned-Prior-Conditioned Flow Matching
Hieu-Nghia Huynh-Nguyen, Ngoc Son Nguyen, Huynh Nguyen Dang +3
Text-to-speech (TTS) systems have seen significant advancements in recent years, driven by improvements in deep learning and neural network architectures. Viewing the output speech…
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…
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…
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…
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,…
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…
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…
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…
Open-Vocabulary Affordance Detection in 3D Point Clouds
Toan Nguyen, Minh Nhat Vu, An Vuong +4
Affordance detection is a challenging problem with a wide variety of robotic applications. Traditional affordance detection methods are limited to a predefined set of affordance la…