用无约束照片集实现户外场景的精准动态光照重渲染。
GaRe: Relightable 3D Gaussian Splatting for Outdoor Scenes from Unconstrained Photo Collections
- 基于图像分解分离阳光、天光与间接光照，支持多光照操控。
- 生成逼真动态阴影，效果优于现有方法，视觉保真度高。
- 适合做户外3D重建与影视级光照编辑的研究者使用。
我们提出一种基于3D Gaussian splatting的户外场景光照重渲染框架，利用内在图像分解技术，从无约束照片集合中精确整合太阳光、天空辐射和间接光照。与以往将每幅图像的全局光照压缩为单一潜在向量的方法不同，本方法可同时实现多样化的阴影调整与动态阴影生成。核心创新包括：(1) 基于残差的太阳可见性提取方法，准确分离直射阳光影响；(2) 基于区域的监督框架，结合结构一致性损失，实现物理可解释且一致的光照分解；(3) 基于光线追踪的阴影模拟技术。大量实验表明，该框架在新视角合成上达到与顶尖光照重渲染方案相当的保真度，并产生更自然、多层次的光照与阴影效果。
原文摘要 · Abstract (English)
We propose a 3D Gaussian splatting-based framework for outdoor relighting that leverages intrinsic image decomposition to precisely integrate sunlight, sky radiance, and indirect lighting from unconstrained photo collections. Unlike prior methods that compress the per-image global illumination into a single latent vector, our approach enables simultaneously diverse shading manipulation and the generation of dynamic shadow effects. This is achieved through three key innovations: (1) a residual-based sun visibility extraction method to accurately separate direct sunlight effects, (2) a region-based supervision framework with a structural consistency loss for physically interpretable and coherent illumination decomposition, and (3) a ray-tracing-based technique for realistic shadow simulation. Extensive experiments demonstrate that our framework synthesizes novel views with competitive fidelity against state-of-the-art relighting solutions and produces more natural and multifaceted illumination and shadow effects.
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