… compressing the geometry of a 3D point cloud. That is, we focus on compressing the points’
… While many published algorithms on 3D point cloud compression have yielded good coding …

… We proposed an efficient learned entropy model for point cloud compression. It adopts a
hierarchical attention structure, which allows us to substantially extend the network depth and …

… Each point in the cloud is associated with its 3D position and its color. We devise a method
to compress the colors in point clouds, which is based on a hierarchical transform and …

… on typical 3D point cloud … point cloud, we propose a hierarchical segmentation scheme
based on mean shift clustering to meet the requirement and facilitate the subsequent compression…

… This section details our improved point cloud geometry compression through the use of
hierarchical prior-based super resolution. The system diagram is illustrated in Fig. 1, which …

… The most popular dynamic methods ignore the characteristics of point clouds and use an …
compression means for dynamic point cloud based on curvature estimation and hierarchical …

… This work presented an embedded coder for point cloud attributes. We proposed to encode
RAHT coefficients with SPIHT and to use as hierarchical set partitions the binary tree that …

… sparse, unstructured, and high-precision 3D points for efficient … point cloud, we propose a
multiscale end-to-end learning framework that hierarchically reconstructs the 3D Point Cloud …

… coding standard that compresses 3D point clouds by projecting them into 2D frames, … that
utilizes hierarchical hexahedron partitioning, adapting to varying point cloud densities and non-…

… Point cloud compression based on hierarchical point clustering. In 2013 Asia-Pacific
Signal and Information Processing Association Annual Summit and Conference. 1–7. …