MSGS: Multispectral 3D Gaussian Splatting

Fuente: arXiv
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Main Authors: Zheng, Iris, Tang, Guojun, Doronin, Alexander, Teal, Paul, Zhang, Fang-Lue
Format: Preprint
Published: 2026
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author Zheng, Iris
Tang, Guojun
Doronin, Alexander
Teal, Paul
Zhang, Fang-Lue
author_facet Zheng, Iris
Tang, Guojun
Doronin, Alexander
Teal, Paul
Zhang, Fang-Lue
contents We present a multispectral extension to 3D Gaussian Splatting (3DGS) for wavelength-aware view synthesis. Each Gaussian is augmented with spectral radiance, represented via per-band spherical harmonics, and optimized under a dual-loss supervision scheme combining RGB and multispectral signals. To improve rendering fidelity, we perform spectral-to-RGB conversion at the pixel level, allowing richer spectral cues to be retained during optimization. Our method is evaluated on both public and self-captured real-world datasets, demonstrating consistent improvements over the RGB-only 3DGS baseline in terms of image quality and spectral consistency. Notably, it excels in challenging scenes involving translucent materials and anisotropic reflections. The proposed approach maintains the compactness and real-time efficiency of 3DGS while laying the foundation for future integration with physically based shading models.
format Preprint
id arxiv_https___arxiv_org_abs_2604_13340
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle MSGS: Multispectral 3D Gaussian Splatting
Zheng, Iris
Tang, Guojun
Doronin, Alexander
Teal, Paul
Zhang, Fang-Lue
Computer Vision and Pattern Recognition
Graphics
I.3.7; I.4.8; I.2.10
We present a multispectral extension to 3D Gaussian Splatting (3DGS) for wavelength-aware view synthesis. Each Gaussian is augmented with spectral radiance, represented via per-band spherical harmonics, and optimized under a dual-loss supervision scheme combining RGB and multispectral signals. To improve rendering fidelity, we perform spectral-to-RGB conversion at the pixel level, allowing richer spectral cues to be retained during optimization. Our method is evaluated on both public and self-captured real-world datasets, demonstrating consistent improvements over the RGB-only 3DGS baseline in terms of image quality and spectral consistency. Notably, it excels in challenging scenes involving translucent materials and anisotropic reflections. The proposed approach maintains the compactness and real-time efficiency of 3DGS while laying the foundation for future integration with physically based shading models.
title MSGS: Multispectral 3D Gaussian Splatting
topic Computer Vision and Pattern Recognition
Graphics
I.3.7; I.4.8; I.2.10
url https://arxiv.org/abs/2604.13340