Inverse path tracing has recently been applied to joint material and lighting estimation, given geometry and multi-view HDR observations of an indoor scene. However, it has two major limitations: path tracing is expensive to compute, and ambiguities exist between reflection and emission. We propose a novel Factorized Inverse Path Tracing (FIPT) method which utilizes a factored light transport formulation and finds emitters driven by rendering errors. Our algorithm enables accurate material and lighting optimization faster than previous work, and is more effective at resolving ambiguities. The exhaustive experiments on synthetic scenes show that our method (1) outperforms state-of-the-art indoor inverse rendering and relighting methods particularly in the presence of complex illumination effects; (2) speeds up inverse path tracing optimization to less than an hour. We further demonstrate robustness to noisy inputs through material and lighting estimates that allow plausible relighting in a real scene. The source code is available at: https://github.com/lwwu2/fipt
翻译:反向路径追踪最近被应用于室内场景的几何和多视角HDR观测的联合材质和照明估计。但它有两个主要限制:路径追踪计算成本高,反射和发射之间存在歧义。我们提出了一种新颖的因式分解的反向路径追踪(FIPT)方法,它利用了因式化的光传输公式,并通过渲染错误发现发射器。我们的算法使得比以前的工作更快更准确地进行材料和照明优化,并更有效地解决歧义。对合成场景的全面实验表明,我们的方法(1)特别在存在复杂照明效果时优于最先进的室内反向渲染和重新照明方法;(2)加速反向路径追踪优化至少需要不到一小时。我们通过允许真实场景中的合理照明得到对嘈杂输入的抗干扰估计的进一步展示。源代码可在https://github.com/lwwu2/fipt 上获得。