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 …

With the proliferation of sensor devices, the extensive utilization of three-dimensional data in
multimedia continues to grow. Point clouds are widely adopted within this domain because …

Point cloud data is pivotal in applications like autonomous driving, virtual reality, and
robotics. However, its substantial volume poses significant challenges in storage and …

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 …

Learning an accurate entropy model is a fundamental way to remove the redundancy in
point cloud compression. Recently, the octree-based auto-regressive entropy model which …

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 …

Occupancy prediction has increasingly garnered attention in recent years for its fine-grained
understanding of 3D scenes. Traditional approaches typically rely on dense, regular grid …

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 …