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ICCV2025Top-tier venue

GaSLight: Gaussian Splats for Spatially-Varying Lighting in HDR

Christophe Bolduc, Yannick Hold-Geoffroy, Jean-François Lalonde

2025Year
14Citations
6Top-tier citations

Abstract

We present GASLIGHT, a method that generates spatiallyvarying lighting from regular images. Our method proposes using HDR Gaussian Splats as light source representation, marking the first time regular images can serve as light sources in a 3D renderer. Our two-stage process first enhances the dynamic range of images plausibly and accurately by leveraging the priors embedded in diffusion models. Next, we employ Gaussian Splats to model 3D lighting, achieving spatially variant lighting. Our approach yields state-of-the-art results on HDR estimations and their applications in illuminating virtual objects and scenes. To facilitate the benchmarking of images as light sources, we introduce a novel dataset of calibrated and unsaturated HDR captures to evaluate images as light sources. We assess our method using a combination of our dataset and an existing dataset from the literature. The code to reproduce our method is available at https://lvsn.github.io/ gaslight/.

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