用普通图像生成3D场景的动态光照，效果领先。
GaSLight: Gaussian Splats for Spatially-Varying Lighting in HDR
- 用扩散模型提升图像动态范围，再以高斯点表示光照。
- 在真实光照重建和虚拟物体照明上达到当前最佳性能。
- 适合做3D渲染、数字孪生的开发者或研究者参考。
我们提出GaSLight，一种从普通图像生成空间变化光照的方法。首次将HDR高斯点作为光源表示，实现用普通图像驱动3D渲染。方法分两阶段：首先利用扩散模型中的先验知识，合理且准确地增强图像动态范围；随后采用高斯点建模3D光照，实现空间变化的光照效果。该方法在HDR估计及虚拟物体与场景照明应用中达到当前最优表现。为便于评估图像作为光源的效果，我们构建了一个新的校准未过曝HDR数据集，并结合文献中现有数据集进行评估。
原文摘要 · Abstract (English)
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/
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。