Title
Ambient lighting generation for flash images with guided conditional adversarial networks
Date Issued
01 January 2020
Access level
metadata only access
Resource Type
conference paper
Publisher(s)
SciTePress
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.
Start page
381
End page
388
Volume
4
Language
English
OCDE Knowledge area
Ciencias de la computación
Scopus EID
2-s2.0-85083578185
Resource of which it is part
VISIGRAPP 2020 - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
ISBN of the container
978-989758402-2
Conference
VISIGRAPP 2020 - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
Sources of information: Directorio de Producción Científica Scopus