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Spectral World Renderer: Unified 3D Hyperspectral Unmixing

Chia-Ming Lee, Yu-Jou Hsiao, Ming-Ching Chang, Xin Li, Yu-Lun Liu, Chih-Chung Hsu

Latestcs.CLcs.LGcs.AIcs.CV
arXiv ID
2610.19520 v1
Category
Submitted
2026-10-14

Abstract

Cameras and the foundation models built on them recognize what a 3D scene contains, but not what it is made of: surfaces of the same colour can be different materials. Hyperspectral unmixing explains each spectrum as a mixture of material signatures, yet in 3D it is applied to rendered images after the views are composited, or tied to slow implicit fields, and no multi-view data with known composition exist to check the result. We present the Spectral World Renderer (SWR), which unifies world generation and unmixing. A coding agent builds executable 3D worlds that are rendered with measured spectra, so every hyperspectral image comes with exact labels and sub-pixel proportions; the resulting SWR-Bench provides eight indoor and outdoor worlds in which decompositions can be verified. SWR then unmixes inside rendering: each Gaussian of a compact 3D representation is decoded into material abundances before compositing, so one render yields spectra and material maps, and any surface can be queried by material name, a clicked pixel or a reference spectrum. Without material labels, SWR identifies materials best in all eight worlds, has the best mean PSNR on real captures, trains 3.7-12.9x faster than unmixing baselines, renders 34.9 labelled views/s and separates same-coloured materials.

Comment: Project page: https://ming053l.github.io/Spectral-World-Renderer/ Code: https://github.com/ming053l/Spectral-World-Renderer Dataset: https://huggingface.co/datasets/ming0531/SWR-Bench

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