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GaSLight: Gaussian Splats for Spatially-Varying Lighting in HDR

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We present GaSLight, a method that generates spatially-varying 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 to evaluate images as light sources. We assess our method using a combination of this novel dataset and an existing dataset from the literature. Project page: https://lvsn.github.io/gaslight/

Christophe Bolduc, Yannick Hold-Geoffroy, Zhixin Shu, Jean-Fran\c{c}ois Lalonde• 2025

Related benchmarks

TaskDatasetResultRank
Visual Quality AssessmentMip-NeRF360
Positive Score47.2
5
Object InsertionLH3D-Ku (test)
PSNR20.41
5
Mesh InsertionLH3D-Blender
PSNR19.171
5
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