  To cope with the challenges that low light conditions produce in images,
photographers tend to use the light provided by the camera flash to get better
illumination. Nevertheless, harsh shadows and non-uniform illumination can
arise from using a camera flash, especially in low light conditions. Previous
studies have focused on normalizing the lighting on flash images; however, to
the best of our knowledge, no prior studies have examined the sideways shadows
removal, reconstruction of overexposed areas, and the generation of synthetic
ambient shadows or natural tone of scene objects. To provide more natural
illumination on flash images and ensure high-frequency details, we propose a
generative adversarial network in a guided conditional mode. We show that this
approach not only generates natural illumination but also attenuates harsh
shadows, simultaneously generating synthetic ambient shadows. Our approach
achieves promising results on a custom FAID dataset, outperforming our baseline
studies. We also analyze the components of our proposal and how they affect the
overall performance and discuss the opportunities for future work.
