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arXiv:1901.04252cs.CV

DeepFlash: Turning a Flash Selfie into a Studio Portrait

Nicola Capece, Francesco Banterle, Paolo Cignoni, Fabio Ganovelli, Roberto Scopigno, Ugo Erra

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Abstract

We present a method for turning a flash selfie taken with a smartphone into a photograph as if it was taken in a studio setting with uniform lighting. Our method uses a convolutional neural network trained on a set of pairs of photographs acquired in an ad-hoc acquisition campaign. Each pair consists of one photograph of a subject's face taken with the camera flash enabled and another one of the same subject in the same pose illuminated using a photographic studio-lighting setup. We show how our method can amend defects introduced by a close-up camera flash, such as specular highlights, shadows, skin shine, and flattened images.

arXiv comments
Journal reference
Elsevier Image Communication, Volume 77, September 2019, Pages 28-39
DOI
doi:10.1016/j.image.2019.05.013
Subjects
cs.CVComputer Vision and Pattern Recognition cs.LGMachine Learning

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  1. Learning to See in the Dark (2018) 1 comment

    • Absolutely! We recently rebranded our AI solutions from ALLIS (Advanced Low Light Imagine Solution) to ALIIS (All Light Intelligent Imaging Solution) specifically because we are beginning to branch out to handle use cases such as this! As a proof of concept that this task can be…

      y7r4mView on HNParent context

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