arXiv Computer Vision
Hybrid-PCGC: Hybrid Point Cloud Geometry Compression Bridging Generalization-based Model and Implicit Neural Representation
Read the original on arXiv Computer Vision →Hybrid-PCGC is a point cloud geometry compression method that blends learned generalization with implicit neural representations. It treats compression as a joint geometry-and-model bitrate allocation problem, optimizing instance‑specific weight offsets as transmitted variables. The approach separates dataset‑agnostic prior modeling from instance‑specific adaptation using a Frozen General Module, a Dual Trainable Adaptive Module, an Adaptive Scope Controller, and a Supervised Offset Compression Module, achieving significant bitrate reductions over existing methods.
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