English

Cross-Spectral Neural Radiance Fields

Computer Vision and Pattern Recognition 2022-09-02 v1

Abstract

We propose X-NeRF, a novel method to learn a Cross-Spectral scene representation given images captured from cameras with different light spectrum sensitivity, based on the Neural Radiance Fields formulation. X-NeRF optimizes camera poses across spectra during training and exploits Normalized Cross-Device Coordinates (NXDC) to render images of different modalities from arbitrary viewpoints, which are aligned and at the same resolution. Experiments on 16 forward-facing scenes, featuring color, multi-spectral and infrared images, confirm the effectiveness of X-NeRF at modeling Cross-Spectral scene representations.

Keywords

Cite

@article{arxiv.2209.00648,
  title  = {Cross-Spectral Neural Radiance Fields},
  author = {Matteo Poggi and Pierluigi Zama Ramirez and Fabio Tosi and Samuele Salti and Stefano Mattoccia and Luigi Di Stefano},
  journal= {arXiv preprint arXiv:2209.00648},
  year   = {2022}
}

Comments

3DV 2022. Project page: https://cvlab-unibo.github.io/xnerf-web/

R2 v1 2026-06-28T00:35:28.889Z