2 citations · 4 across the 8 of their papers we have counts for
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cs.CV2024
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…
cs.RO2024★ 1 cited
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…
cs.RO2024★ 1 cited
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…