用神经光路缓存实现多视角光传播视频的物理级逆渲染。
Neural Inverse Rendering from Propagating Light
- 基于时序扩展的神经辐射缓存，高效模拟光在场景中的多路径传播。
- 在强间接光照下实现当前最优3D重建精度，还原真实光效细节。
- 支持光场重照明、直接/间接光分离，适合影视特效与数字孪生应用。
我们提出首个基于物理的、从多视角光传播视频进行神经逆渲染的系统。方法基于神经辐射缓存的时间分辨扩展——该技术通过存储任意点从任意方向到达的无限次反弹辐射，加速逆渲染过程。所提模型能准确建模直接与间接光传输效应；应用于闪光激光雷达系统的实测数据时，可在强间接光条件下实现当前最优的3D重建效果。此外，我们还展示了光传播的视图合成、实测数据中直接与间接光成分的自动分解，以及多视角时序重照明等新能力。
原文摘要 · Abstract (English)
We present the first system for physically based, neural inverse rendering from multi-viewpoint videos of propagating light. Our approach relies on a time-resolved extension of neural radiance caching -- a technique that accelerates inverse rendering by storing infinite-bounce radiance arriving at any point from any direction. The resulting model accurately accounts for direct and indirect light transport effects and, when applied to captured measurements from a flash lidar system, enables state-of-the-art 3D reconstruction in the presence of strong indirect light. Further, we demonstrate view synthesis of propagating light, automatic decomposition of captured measurements into direct and indirect components, as well as novel capabilities such as multi-view time-resolved relighting of captured scenes.
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