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May, 2024
基于范围图像的点云分割中缺失值的填充的重要性
Filling Missing Values Matters for Range Image-Based Point Cloud Segmentation
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Bike Chen, Chen Gong, Juha Röning
TL;DR
点云分割在机器人感知和导航任务中起着重要作用,本文提出了一种新的投影方法,以及简单有效的填充方法,并介绍了两个网络模型,通过采用这些方法,现有的基于范围图像的点云分割模型在性能上取得了明显的改善。
Abstract
point cloud segmentation
(PCS) plays an essential role in robot perception and navigation tasks. To efficiently understand large-scale outdoor point clouds, their
range image
representation is commonly adopted. T
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