8 citations · 9 across the 8 of their papers we have counts for
8 papers
GAP-RL: Grasps As Points for RL Towards Dynamic Object Grasping
Pengwei Xie, Siang Chen, Qianrun Chen +5
Dynamic grasping of moving objects in complex, continuous motion scenarios remains challenging. Reinforcement Learning (RL) has been applied in various robotic manipulation tasks,…
Target-Oriented Object Grasping via Multimodal Human Guidance
Pengwei Xie, Siang Chen, Dingchang Hu +3
In the context of human-robot interaction and collaboration scenarios, robotic grasping still encounters numerous challenges. Traditional grasp detection methods generally analyze…
Region-aware Grasp Framework with Normalized Grasp Space for Efficient 6-DoF Grasping
Siang Chen, Pengwei Xie, Wei Tang +3
A series of region-based methods succeed in extracting regional features and enhancing grasp detection quality. However, faced with a cluttered scene with potential collision, the…
Part-Guided 3D RL for Sim2Real Articulated Object Manipulation
Pengwei Xie, Rui Chen, Siang Chen +6
Manipulating unseen articulated objects through visual feedback is a critical but challenging task for real robots. Existing learning-based solutions mainly focus on visual afforda…
Category-Agnostic Pose Estimation for Point Clouds
Bowen Liu, Wei Liu, Siang Chen +2
The goal of object pose estimation is to visually determine the pose of a specific object in the RGB-D input. Unfortunately, when faced with new categories, both instance-based and…
Rethinking 6-Dof Grasp Detection: A Flexible Framework for High-Quality Grasping
Pengwei Xie, Siang Chen, Wei Tang +3
Robotic grasping is a primitive skill for complex tasks and is fundamental to intelligence. For general 6-Dof grasping, most previous methods directly extract scene-level semantic…
GenH2R: Learning Generalizable Human-to-Robot Handover via Scalable Simulation, Demonstration, and Imitation
Zifan Wang, Junyu Chen, Ziqing Chen +3
This paper presents GenH2R, a framework for learning generalizable vision-based human-to-robot (H2R) handover skills. The goal is to equip robots with the ability to reliably recei…
Master-Auxiliary: an efficient aggregation strategy for video anomaly detection
Zhiguo Wang, Zhongliang Yang, Yujin Zhang
The aim of surveillance video anomaly detection is to detect events that rarely or never happened in a certain scene. Generally, different detectors can detect different anomalies.…