67 citations · 73 across the 10 of their papers we have counts for
11 papers
MFlowHOI: Whole-Body Human-Object Interaction Generation via Part-Aware MeanFlow
Qiang He, Yonghao Zhang, Yinda Zhang +7
Whole-body human-object interaction (HOI) generation requires coordinating body and finger motion, object trajectories, and time-varying contacts. Existing methods typically rely o…
ViSR-KGC: Visual Subgraph Reasoning with Vision-Language Models for Multimodal Knowledge Graph Completion
Jiafan Li, Mengxue Yang, Jiaqi Zhu +3
Knowledge graph completion (KGC) aims to infer missing entities or relations from incomplete graph structures, and has evolved into multimodal knowledge graph completion (MMKGC), w…
TCATSeg: A Tooth Center-Wise Attention Network for 3D Dental Model Semantic Segmentation
Qiang He, Wentian Qu, Jiajia Dai +9
Accurate semantic segmentation of 3D dental models is essential for digital dentistry applications such as orthodontics and dental implants. However, due to complex tooth arrangeme…
BFA++: Hierarchical Best-Feature-Aware Token Prune for Multi-View Vision Language Action Model
Haosheng Li, Weixin Mao, Zihan Lan +6
Vision-Language-Action (VLA) models have achieved significant breakthroughs by leveraging Large Vision Language Models (VLMs) to jointly interpret instructions and visual inputs. H…
HOGSA: Bimanual Hand-Object Interaction Understanding with 3D Gaussian Splatting Based Data Augmentation
Wentian Qu, Jiahe Li, Jian Cheng +6
Understanding of bimanual hand-object interaction plays an important role in robotics and virtual reality. However, due to significant occlusions between hands and object as well a…
Universal Features Guided Zero-Shot Category-Level Object Pose Estimation
Wentian Qu, Chenyu Meng, Heng Li +6
Object pose estimation, crucial in computer vision and robotics applications, faces challenges with the diversity of unseen categories. We propose a zero-shot method to achieve cat…
Diffgrasp: Whole-Body Grasping Synthesis Guided by Object Motion Using a Diffusion Model
Yonghao Zhang, Qiang He, Yanguang Wan +4
Generating high-quality whole-body human object interaction motion sequences is becoming increasingly important in various fields such as animation, VR/AR, and robotics. The main c…
Multi-GraspLLM: A Multimodal LLM for Multi-Hand Semantic Guided Grasp Generation
Haosheng Li, Weixin Mao, Weipeng Deng +7
Multi-hand semantic grasp generation aims to generate feasible and semantically appropriate grasp poses for different robotic hands based on natural language instructions. Although…
SegGrasp: Zero-Shot Task-Oriented Grasping via Semantic and Geometric Guided Segmentation
Haosheng Li, Weixin Mao, Weipeng Deng +7
Task-oriented grasping, which involves grasping specific parts of objects based on their functions, is crucial for developing advanced robotic systems capable of performing complex…
Hand3D: Hand Pose Estimation using 3D Neural Network
Xiaoming Deng, Shuo Yang, Yinda Zhang +3
We propose a novel 3D neural network architecture for 3D hand pose estimation from a single depth image. Different from previous works that mostly run on 2D depth image domain and…
Joint Hand Detection and Rotation Estimation by Using CNN
Xiaoming Deng, Ye Yuan, Yinda Zhang +4
Hand detection is essential for many hand related tasks, e.g. parsing hand pose, understanding gesture, which are extremely useful for robotics and human-computer interaction. Howe…