Efficient Compression of Structured and Unstructured Volumes via Learned 3D Gaussian Representation
arXiv·low signal
This paper (2607.01164, cs.LG) builds on implicit neural representations to compress structured and unstructured volumetric data using a learned 3D Gaussian representation. Of interest to practitioners working on scientific visualization and large-volume data storage where INR-based compression is emerging.