Point clouds are becoming essential in key applications with advances in capture
technologies leading to large volumes of data. Compression is thus essential for storage …

This paper presents a novel end-to-end Learned Point Cloud Geometry Compression (aka,
Learned-PCGC) system, leveraging stacked Deep Neural Networks (DNN) based …

Recent years have witnessed the growth of point cloud based applications for both
immersive media as well as 3D sensing for auto-driving, because of its realistic and fine …

The emergence of 3D point clouds (3DPCs) is promoting the rapid development of
immersive communication, autonomous driving, and so on. Due to the huge data volume …

摘要随着传感器技术的不断发展, 三维点云被广泛应用于自动驾驶, 机器人, 遥感, 文物修复,
增**现实, 虚拟现实等领域的视觉任务中. 然而, 直接应用收集到的海量原始点云数据得到的效果 …

Point cloud compression with a higher compression ratio and tiny loss is essential for
efficient data transportation. However, previous methods that depend on 3D convolution or …

A learning-based YOGA (Yet Another Geometry-based Point Cloud Compressor) is
proposed. It is flexible, allowing for the separable lossy compression of geometry and color …

Since the development of 3D applications, the point cloud, as a spatial description easily
acquired by sensors, has been widely used in multiple areas such as SLAM and 3D …

Compressing point cloud geometry (PCG) efficiently is of great interests for enabling
abundant networked applications, because PCG is a promising representation to precisely …

The ever-increasing 3D application makes the point cloud compression unprecedentedly
important and needed. In this paper, we propose a patch-based compression process using …