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 …

In point cloud compression, sufficient contexts are significant for modeling the point cloud
distribution. However, the contexts gathered by the previous voxel-based methods decrease …

3D point clouds have found a wide variety of applications in multimedia processing, remote
sensing, and scientific computing. Although most point cloud processing systems are …

This study develops a unified Point Cloud Geometry (PCG) compression method through the
processing of multiscale sparse tensor-based voxelized PCG. We call this compression …

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 …

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

Efficient point cloud compression is fundamental to enable the deployment of virtual and
mixed reality applications, since the number of points to code can range in the order of …

Point cloud based 3D visual representation is becoming popular due to its ability to exhibit
the real world in a more comprehensive and immersive way. However, under a limited …

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 …

In recent years, we have witnessed the presence of point cloud data in many aspects of our
life, from immersive media, autonomous driving to healthcare, although at the cost of a …