AI RESEARCH
Octree-based Learned Point Cloud Geometry Compression: A Lossy Perspective
arXiv CS.CV
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ArXi:2603.28095v1 Announce Type: new Octree-based context learning has recently become a leading method in point cloud compression. However, its potential on lossy compression remains undiscovered. The traditional lossy compression paradigm using lossless octree representation with quantization step adjustment may result in severe distortions due to massive missing points in quantization. Therefore, we analyze data characteristics of different point clouds and propose lossy approaches specifically.