A Dataset of Flash and Ambient Illumination Pairs from the Crowd

  • Yağız AksoyEmail author
  • Changil Kim
  • Petr Kellnhofer
  • Sylvain Paris
  • Mohamed Elgharib
  • Marc Pollefeys
  • Wojciech Matusik
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11213)


Illumination is a critical element of photography and is essential for many computer vision tasks. Flash light is unique in the sense that it is a widely available tool for easily manipulating the scene illumination. We present a dataset of thousands of ambient and flash illumination pairs to enable studying flash photography and other applications that can benefit from having separate illuminations. Different than the typical use of crowdsourcing in generating computer vision datasets, we make use of the crowd to directly take the photographs that make up our dataset. As a result, our dataset covers a wide variety of scenes captured by many casual photographers. We detail the advantages and challenges of our approach to crowdsourcing as well as the computational effort to generate completely separate flash illuminations from the ambient light in an uncontrolled setup. We present a brief examination of illumination decomposition, a challenging and underconstrained problem in flash photography, to demonstrate the use of our dataset in a data-driven approach.


Flash photography Dataset collection Crowdsourcing Illumination decomposition 



We would like to thank Alexandre Kaspar for his support on crowdsourcing, James Minor and Valentin Deschaintre for their feedback on the text, and Michaël Gharbi for our discussions. Y. Aksoy was supported by QCRI-CSAIL Computer Science Research Program at MIT, and C. Kim was supported by Swiss National Science Foundation fellowship P2EZP2 168785.

Supplementary material

474192_1_En_39_MOESM1_ESM.pdf (1.5 mb)
Supplementary material 1 (pdf 1585 KB)
474192_1_En_39_MOESM2_ESM.pdf (1.6 mb)
Supplementary material 2 (pdf 1614 KB)


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Yağız Aksoy
    • 1
    • 2
    Email author
  • Changil Kim
    • 1
  • Petr Kellnhofer
    • 1
  • Sylvain Paris
    • 3
  • Mohamed Elgharib
    • 4
  • Marc Pollefeys
    • 2
    • 5
  • Wojciech Matusik
    • 1
  1. 1.MIT CSAILCambridgeUSA
  2. 2.ETH ZürichZürichSwitzerland
  3. 3.Adobe ResearchCambridgeUSA
  4. 4.QCRIDohaQatar
  5. 5.MicrosoftRedmondUSA

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