Recovering lighting in a scene from a single image is a fundamental problem in computer vision. While a mirror ball light probe can capture omnidirectional lighting, light probes are generally unavailable in everyday images. In this work, we study recovering lighting from accidental light probes (ALPs) -- common, shiny objects like Coke cans, which often accidentally appear in daily scenes. We propose a physically-based approach to model ALPs and estimate lighting from their appearances in single images. The main idea is to model the appearance of ALPs by photogrammetrically principled shading and to invert this process via differentiable rendering to recover incidental illumination. We demonstrate that we can put an ALP into a scene to allow high-fidelity lighting estimation. Our model can also recover lighting for existing images that happen to contain an ALP.

翻译：从单张图像中恢复场景光照是计算机视觉中的一个基本问题。虽然镜面球光探针能够捕捉全方位光照，但日常图像中通常不存在光探针。本研究探索从偶然光探针（ALP）——日常场景中偶然出现的常见反光物体（如可乐罐）——中恢复光照。我们提出一种基于物理的方法对ALP进行建模，并从其单张图像的外观中估计光照。核心思想是通过摄影测量原理的着色对ALP外观进行建模，并通过可微分渲染逆推该过程以恢复偶然光照。实验证明，在场景中引入ALP可实现高保真光照估计；同时，我们的模型也能对恰好包含ALP的现有图像进行光照恢复。