Experiments on Deep Single-Image Portrait Relighting
Quentin Bammey
published
2022-10-12
reference
Quentin Bammey, Experiments on Deep Single-Image Portrait Relighting, Image Processing On Line, 12 (2022), pp. 420–434. https://doi.org/10.5201/ipol.2022.429

Communicated by Jean-Michel Morel
Demo edited by Quentin Bammey

Abstract

This work describes deep single-image portrait relighting, a method to change the lighting of an image. The method is based on an hourglass convolutional neural network, which encodes the image and its estimated original lighting features, then replaces the lighting features with the target light. We highlight the overall good results produced by this method, as well as its limitations and the lighting artifacts that sometimes appear on relighted images.

This is an MLBriefs article, the source code has not been reviewed!
The original source code is available here (last checked 2022/10/10).

Download

History