Accidental Light Probes（偶然光探针）
Accidental Light Probes
AI总结：
该研究针对单图场景光照恢复问题，提出基于物理的方法对日常场景中常见的闪亮偶然光探针（ALPs）建模，通过可微渲染反演实现高保真光照估计，可用于含ALP的现有图像。
摘要：
从单张图像恢复场景光照是计算机视觉中的一个基础问题。虽然镜面球光探针能够捕获全向光照，但日常图像中通常不存在光探针。在本研究中，我们针对偶然光探针（ALPs，即可乐罐这类常见的闪亮物体，常意外出现在日常场景中）开展光照恢复研究。我们提出一种基于物理的方法对ALPs建模，并根据其在单张图像中的外观估计光照。核心思路是通过符合摄影测量原理的着色模型模拟ALPs的外观，再通过可微渲染反转该过程以恢复附带光照。我们验证了将ALP放入场景可实现高保真光照估计，我们的模型还能为恰好包含ALP的现有图像恢复光照。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
