Accidental Light Probes

Hong-Xing Yu, Samir Agarwala, Charles Herrmann, R. Szeliski, Noah Snavely +2 more
2/14/2026

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Abstract

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 photogram-metrically 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**Project website: https://kovenyu.com/ALP. I'd rather be Shiny. - Tamatoa from Moana, 2016

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Cite this paper

@article{yu2026accidental,
  title  = {Accidental Light Probes},
  author = {Hong-Xing Yu and Samir Agarwala and Charles Herrmann and R. Szeliski and Noah Snavely and Jiajun Wu and Deqing Sun},
  year   = {2026},
  eprint = {2301.05211},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/2301.05211},
  journal = {CVPR 2023 2023}
}

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