让3D高斯泼溅在复杂光照下仍能生成高质量新视角图像
Luminance-GS: Adapting 3D Gaussian Splatting to Challenging Lighting Conditions with View-Adaptive Curve Adjustment
- 为每个视角动态调整颜色矩阵和亮度曲线
- 在低光、过曝等条件下实现顶尖重建质量
- 无需修改原有3DGS结构，支持实时渲染
在多视角场景中，自然光照（如弱光）和相机曝光设置（如曝光时间）会显著影响图像质量，导致不同视角间出现光度不一致。这类光照退化与视角依赖性变化给基于神经辐射场（NeRF）和3D高斯泼溅（3DGS）的新视角合成框架带来巨大挑战。为此，我们提出Luminance-GS，一种在多样复杂光照条件下实现高质量新视角合成的3DGS改进方法。通过采用逐视图颜色矩阵映射与视图自适应曲线调整，Luminance-GS在低光、过曝及不同曝光条件下的表现均达到当前最优（SOTA），且不改变原始3DGS显式表示。相比以往基于NeRF和3DGS的基线方法，Luminance-GS兼具实时渲染速度与更优重建质量。
原文摘要 · Abstract (English)
Capturing high-quality photographs under diverse real-world lighting conditions is challenging, as both natural lighting (e.g., low-light) and camera exposure settings (e.g., exposure time) significantly impact image quality. This challenge becomes more pronounced in multi-view scenarios, where variations in lighting and image signal processor (ISP) settings across viewpoints introduce photometric inconsistencies. Such lighting degradations and view-dependent variations pose substantial challenges to novel view synthesis (NVS) frameworks based on Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS). To address this, we introduce Luminance-GS, a novel approach to achieving high-quality novel view synthesis results under diverse challenging lighting conditions using 3DGS. By adopting per-view color matrix mapping and view-adaptive curve adjustments, Luminance-GS achieves state-of-the-art (SOTA) results across various lighting conditions -- including low-light, overexposure, and varying exposure -- while not altering the original 3DGS explicit representation. Compared to previous NeRF- and 3DGS-based baselines, Luminance-GS provides real-time rendering speed with improved reconstruction quality.
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