  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.
