计算机与数字工程2026，Vol.54Issue(6)：1558-1562,1618,6.DOI:10.3969/j.issn.1672-9722.2026.06.003
基于注意机制的多级点云补全算法
A Multi-stage Point Cloud Completion Algorithm Based on Attention Mechanism
摘要
Abstract
In response to the problem of restoring blurry details and low utilization of raw input geometry in some point cloud completion algorithms based on point cloud form,a multi-stage point cloud completion algorithm based on attention mechanism is proposed.Firstly,the original point cloud is input and the point feature matrix is output through a two-layer point network.Then,an attention mechanism is used to reevaluate the weight of the point feature matrix,obtain a new point feature matrix,and aggregate the final global feature vector.Next,the global feature vector is input into the fully connected layer and dilation penalty is used to ob-tain a rough output point cloud.Finally,the rough point cloud generated by the fully connected layer is combined and sampled again with the original input point cloud,and a dense point cloud model is obtained through folding the network.The algorithm designed in this article is tested on the ShapeNet dataset,and the experimental results show that the algorithm can effectively complete point cloud details,it has strong detail restoration ability,and good robustness to noise.关键词
补全算法/注意机制/三维点云Key words
completion algorithm/attention mechanism/3D point cloud分类
信息技术与安全科学引用本文复制引用
臧强,郭镜虹,孙续文,刘云平..基于注意机制的多级点云补全算法[J].计算机与数字工程,2026,54(6):1558-1562,1618,6.基金项目
国家自然科学基金项目(编号:61973170,51875293,51575283) （编号:61973170,51875293,51575283）
国家重点研发计划项目(编号:2017YFD0701201-02) （编号:2017YFD0701201-02）
2021年度全国教育科学国防军事教育学科规划课题(编号:JYKYC2021018)资助. （编号:JYKYC2021018）
