SpectralSplat: Appearance-Disentangled Feed-Forward Gaussian Splatting for Driving Scenes
Feed-forward 3D Gaussian Splatting methods have achieved impressive reconstruction quality for autonomous driving scenes, yet they entangle scene geometry with transient appearance properties such as lighting, weather, and time of day. This coupling prevents relighting, appearance transfer, and consistent rendering across multi-traversal data captured under varying environmental conditions. We present SpectralSplat, a method that disentangles appearance from geometry within a feed-forward Gaussian Splatting framework. Our key insight is to factor color prediction into an appearance-agnostic base stream and and appearance-conditioned adapted stream, both produced by a shared MLP conditione...
| Authors | Quentin Herau, Tianshuo Xu, Depu Meng et al. |
|---|---|
| Primary category | cs.CV |
| Published | 3 April 2026 |
| Last updated at source | 3 April 2026 |
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