Less-parametric point cloud upsampling network
简介：In the field of aircraft design and maintenance,with the innovation of cabin cable three-dimensional(3D)scanning and sensor technology,high-precision cabin point cloud data has become the key to improving the accuracy of cabin navigation and building a realistic virtual re-ality environment.In the face of largescale point cloud data,how to efficiently and uniformly construct a realistic virtual reality environ-ment has become a challenge.In this paper,we propose a new low-parametric point cloud upsampling network(LPNet),which is based on the no-learn model to learn the complementary geometric knowledge between point clouds based on some simple data transforma-tions,to efficiently retain the geometric properties of point clouds,and then input the results into the up-sampling module,and simply in-sert a few layers of multilayer perceptron(MLP)to efficiently generate high-resolution point clouds.It is able to efficiently generate high-resolution point clouds,showing great flexibility and realizing the efficient use of computational resources.展开
学者：AihuaLingHongfangLiuJunwenWangRuyu
关键词：pointnetworkcloudless-parametricupsampling
在线出版日期：2026-03-11 （网站首发日期）
