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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…