Deep Flash : Turning a Flash Selfie Into a Studio Portrait

Abstract

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. Website to the official publication: Signal Processing: Image Communication. DOI: 10.1016/j.image.2019.05.013. Results Samples of validation data. Each group of images is composed of: the original image taken with the smartphone flash (top left); the flash image to which the bilateral filter was applied (bottom left); the image reconstructed by the difference prediction of the CNN (center); the ground truth reconstructed (top right); the ground truth (bottom right). \revision{The SSIM was computed by comparing the central image of each group and the image at top right.

10.1016/j.image.2019.05.013

Francesco Banterle
Francesco Banterle
Researcher

Researcher at the Visual Computing Lab

Paolo Cignoni
Paolo Cignoni
Research Director
Fabio Ganovelli
Fabio Ganovelli
Senior Researcher

Senior Researcher at the Visual Computing Lab