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http://hdl.handle.net/20.500.12390/2647


Título: Ambient lighting generation for flash images with guided conditional adversarial networks
Autor(es): Chávez J. 
Mora R. 
Cayllahua-Cahuina E. 
Resumen: 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.
Tema: Ambient Images;Attention Map;Flash Images;Generative Adversarial Networks;Illumination
Editorial: SciTePress
Fecha de publicación: 2020
Publicado en: VISIGRAPP 2020 - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications 
Financiamiento: CONV-000234-2015-FONDECYT-DE - PROMOCION 1 
Tipo de publicación: info:eu-repo/semantics/article
Identificador Handle: http://hdl.handle.net/20.500.12390/2647
Nivel de acceso: info:eu-repo/semantics/closedAccess
Colección:2.2 Estudios de maestría

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marcado en 27-nov-2021

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