The large data volume of point clouds poses severe challenges for efficient storage and
transmission in recent years. In this paper, we propose the first--to our best knowledge--end …

Point cloud is a set of three-dimensional points in arbitrary order, which is a popular
representation of 3D scene in autonomous navigation and immersive applications in recent …

With the development of visualization technology, the amount of geological data information
is increasing, and the interactive display of big data faces severe challenges. Because …

In recent years, the diffusion-based image compression scheme has achieved significant
success, which inspires us to use diffusion theory to employ the diffusion model for point …

The nonuniform distribution of points in a point cloud and their abundant attribute
information (such as colour, reflectance, and normal) result in the generation of massive …

The plenoptic point cloud that has multiple colors from various directions, is a more complete
representation than the general point cloud that usually has only one color. It is more …

Learning-based methods have proven successful in compressing geometric information for
point clouds. For attribute compression, however, they still lag behind non-learning-based …

三维点云为物理世界精细数字化提供了高精度的三维表达方式, 广泛应用于三维建模, 智慧城市,
自主导航系统, 增强现实等领域. 然而点云的数据海量, 非结构化, 密度不均等特点给点云的存储 …

Modern laser scanners, depth sensor devices and Dense Image Matching techniques allow
for capturing of extensive point cloud datasets. While capturing has become more user …

Visual information can be captured in both 2D and 3D formats. For example, an image is a
2D representation while a point cloud is a 3D representation. A sequence of images …