arXiv Computer Vision
Sep 25

Towards Practical Compression of 3D Gaussian Splatting

The paper introduces COSA-GS, a new compression method for 3D Gaussian Splatting that avoids spatial aggregation by using anchor-wise causal factorization. It builds a compact learnable anchor latent from geometry context and fuses it with the geometry context to create an anchor context for attribute coding, employing only linear transformations and activations. The method is trained with rate–distortion optimization, adaptive Gaussian pruning, and quantization-aware training to ensure bit‑exact entropy decoding across platforms, achieving state‑of‑the‑art compression performance with fast, consistent cross‑platform decoding.

By Pengpeng Yu, Yueru Chen, Fei Song, Tai Qin, Qi Zhang, Jing Wang, Yulan Guo
arXiv Computer Vision
4d ago

Gaussian Splatting-based Volumetric Video Compression with Sparse 4D Anchors

The paper introduces SAGA, a volumetric video codec that uses sparse 4D anchors to guide Gaussian splatting for dynamic scene representation. By hierarchically arranging anchors and employing coordinate‑based INR decoders, SAGA shares geometry and appearance across primitives, captures long‑range dependencies with an orthogonality‑informed slot‑update strategy, and achieves substantial BD‑rate reductions on the Neu3D test set.

By Ge Gao, Siyue Teng, Chanqgi Wang, Fan Zhang, Nantheera Anantrasirichai, Jui Chiu Chiang, Wen-Hsiao Peng, David Bull