Can I read ReFiNe: Recursive Field Networks for Cross-modal Multi-scene Representation on EtoBox?

ReFiNe: Recursive Field Networks for Cross-modal Multi-scene Representation by Zakharov, Sergey; Liu, Katherine; Gaidon, Adrien; Ambrus, Rares is a scholarly article available to read on EtoBox.

What is ReFiNe: Recursive Field Networks for Cross-modal Multi-scene Representation about?

The common trade-offs of state-of-the-art methods for multi-shape representation (a single model "packing" multiple objects) involve trading modeling accuracy against memory and storage. We show how to encode multiple shapes represented as continuous neural fields with a higher degree of precision than previously possible and with low memory usage. Key to our approach is a recursive hierarchical formulation that exploits object self-similarity, leading to a highly compressed and efficient shape latent space. Thanks to the recursive formulation, our method supports spatial and global-to-local latent feature fusion without needing to initialize and maintain auxiliary data structures, while still allowing for continuous field queries to enable applications such as raytracing. In experiments on a set of diverse datasets, we provide compelling qualitative results and demonstrate state-of-the-art multi-scene reconstruction and compression results with a single network per dataset.

Author

Zakharov, Sergey; Liu, Katherine; Gaidon, Adrien; Ambrus, Rares

Published

2024

Language

EN