Leveraging Diffusion Models for Robust and Generalizable Single-Image Lighting Estimation

We present a simple yet effective technique to estimate lighting in a single input image by leveraging pre-trained diffusion models to render a chrome ball into the scene. Our method produces convincing light estimates across diverse settings and demonstrates superior generalization to in-the-wild scenarios.