Ambient Lighting Generation for Flash Images with Guided Conditional Adversarial Networks

José Chávez, Rensso Mora, Edward Cayllahua-Cahuina

2020

Abstract

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.

Paper Citation

in Harvard Style

Chávez J., Mora R. and Cayllahua-Cahuina E. (2020). Ambient Lighting Generation for Flash Images with Guided Conditional Adversarial Networks. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP; ISBN 978-989-758-402-2, SciTePress, pages 381-388. DOI: 10.5220/0008983603810388

in Bibtex Style

@conference{visapp20,
author={José Chávez and Rensso Mora and Edward Cayllahua-Cahuina},
title={Ambient Lighting Generation for Flash Images with Guided Conditional Adversarial Networks},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP},
year={2020},
pages={381-388},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008983603810388},
isbn={978-989-758-402-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP
TI - Ambient Lighting Generation for Flash Images with Guided Conditional Adversarial Networks
SN - 978-989-758-402-2
AU - Chávez J.
AU - Mora R.
AU - Cayllahua-Cahuina E.
PY - 2020
SP - 381
EP - 388
DO - 10.5220/0008983603810388
PB - SciTePress