Discrete point cloud objects lack sufficient shape descriptors of 3D geometries. In this paper,
we present a novel method for aggregating hypothetical curves in point clouds. Sequences …

Abstract 3D models are used in a variety of CAX fields, and their key is 3D data geometry
and semantic perception. However, semantic learning of 3D point clouds is a challenge due …

Remarkable performance from Transformer networks in Natural Language Processing
promote the development of these models in dealing with computer vision tasks such as …

Recently, a lot of attention is given to deep learning on raw 3D point clouds. Existing
approaches, however, either exploit the global shape feature without paying attention to the …

Registering urban point clouds is a pretty challenging task due to the large-scale, noise and
data incompleteness of LiDAR scanning data. In this paper, we propose SARNet, a novel …

Effectively integrating the local features and their spatial distribution information for more
effective point cloud analysis is a subject that has been explored for a long time. Inspired by …

Fully exploring the correlation of local features and their spatial distribution in point clouds is
essential for feature modeling. This paper, inspired by convolutional neural networks …

摘要与密集网格表示的图像不同, 点云自身具有不规则和无序性的特点, 因而如何准确地推理出
点云数据中的形状特征是一项具有挑战性的工作. 为解决当前研究存在的不足, 提出了点集内 …

摘要目的3 维点云是编码几何信息的主要数据结构, 与2 维视觉数据不同的是, 点云中隐藏了3
维物体中重要的形状特征. 为更好地从无序的点云中挖掘形状特征, 本文提出一种能够端到端且 …

针对现有主流网络对于点云局部特征提取的能力不足, 以及在特征提取过程中未考虑点云密度的
问题, 提出一种密度导向的点云动态图卷积网络. 首先提出点云局部密度指数的概念 …