Efficient and Generic Point Model for Lossless Point Cloud Attribute Compression

arXiv:2404.06936v1 Announce Type: new
Abstract: The past several years have witnessed the emergence of learned point cloud compression (PCC) techniques. However, current learning-based lossless point cloud attribute compression (PCAC) methods either suffer from high computational complexity or deteriorated compression performance. Moreover, the significant variations in point cloud scale and sparsity encountered in real-world applications make developing an all-in-one neural model a challenging task. In this paper, we propose PoLoPCAC, an efficient and generic lossless PCAC method that achieves high compression …

arxiv cloud compression cs.cv cs.mm type