Deep Single-Image Portrait Relighting

ICCV 2019

Publication date: October 27, 2019

Hao Zhou, Sunil Hadap, Kalyan Sunkavalli, David Jacobs

In this work, we design a single portrait relighting algorithm. We first apply a physically-based portrait relighting method to generate a large scale, high quality, "in the wild" portrait relighting dataset (DPR). A deep Convolutional Neural Network (CNN) is then trained using this dataset to generate a relighted portrait image by using a source image and a target lighting as input. Our trained network can relight portrait images with resolutions as high as 1024 X 1024.

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