3 papers
cs.CV2025
Learning effective pruning at initialization from iterative pruning
Shengkai Liu, Yaofeng Cheng, Fusheng Zha +4
Pruning at initialization (PaI) reduces training costs by removing weights before training, which becomes increasingly crucial with the growing network size. However, current PaI m…
cs.CV2025
Rethinking Transparent Object Grasping: Depth Completion with Monocular Depth Estimation and Instance Mask
Yaofeng Cheng, Xinkai Gao, Sen Zhang +4
Due to the optical properties, transparent objects often lead depth cameras to generate incomplete or invalid depth data, which in turn reduces the accuracy and reliability of robo…
cs.RO2025
PCF-Grasp: Converting Point Completion to Geometry Feature to Enhance 6-DoF Grasp
Yaofeng Cheng, Fusheng Zha, Wei Guo +4
The 6-Degree of Freedom (DoF) grasp method based on point clouds has shown significant potential in enabling robots to grasp target objects. However, most existing methods are base…