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.
Cite
@article{arxiv.1901.04252,
title = {DeepFlash: Turning a Flash Selfie into a Studio Portrait},
author = {Nicola Capece and Francesco Banterle and Paolo Cignoni and Fabio Ganovelli and Roberto Scopigno and Ugo Erra},
journal= {arXiv preprint arXiv:1901.04252},
year = {2019}
}