Search Results for author: Hongjie Fang

Found 4 papers, 2 papers with code

Target-Referenced Reactive Grasping for Dynamic Objects

no code implementations CVPR 2023 Jirong Liu, Ruo Zhang, Hao-Shu Fang, Minghao Gou, Hongjie Fang, Chenxi Wang, Sheng Xu, Hengxu Yan, Cewu Lu

Reactive grasping, which enables the robot to successfully grasp dynamic moving objects, is of great interest in robotics.

TransCG: A Large-Scale Real-World Dataset for Transparent Object Depth Completion and a Grasping Baseline

1 code implementation17 Feb 2022 Hongjie Fang, Hao-Shu Fang, Sheng Xu, Cewu Lu

However, the majority of current grasping algorithms would fail in this case since they heavily rely on the depth image, while ordinary depth sensors usually fail to produce accurate depth information for transparent objects owing to the reflection and refraction of light.

Depth Completion Robotic Grasping +2

Graspness Discovery in Clutters for Fast and Accurate Grasp Detection

1 code implementation ICCV 2021 Chenxi Wang, Hao-Shu Fang, Minghao Gou, Hongjie Fang, Jin Gao, Cewu Lu

To quickly detect graspness in practice, we develop a neural network named graspness model to approximate the searching process.

Robotic Grasping

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