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 …

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 …

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 …

With the rise of immersive media applications such as digital museums, virtual reality, and
interactive exhibitions, point clouds, as a three-dimensional data storage format, have …

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 …

This paper gives an overview of OpenPointCloud, the first open-source algorithm library
containing outstanding deep learning methods on point cloud compression (PCC). We …

Learning-based point cloud compression has exhibited superior coding performance over
the traditional methods such as MEPG G-PCC. Considering that conventional point cloud …

A universal multiscale conditional coding framework, Unicorn, is proposed to compress the
geometry and attribute of any given point cloud. Geometry compression is addressed in Part …

In point cloud geometry compression, context models usually use the one-hot encoding of
node occupancy as the label, and the cross-entropy between the one-hot encoding and the …