Bienvenido al Repositorio Institucional del Concytec

El Repositorio Institucional del Concytec tiene como objetivo permitir el libre acceso a la producción científica institucional, optimizando su visibilidad; así mismo garantizar la preservación y conservación de la información relacionada a la ciencia, tecnología e innovación.



Display.item.jsp


Por favor, utiliza este identificador para citar o enlazar este ítem:
http://hdl.handle.net/20.500.12390/2647


Campo DCValorIdioma
dc.contributor.authorChávez J.es_PE
dc.contributor.authorMora R.es_PE
dc.contributor.authorCayllahua-Cahuina E.es_PE
dc.date.accessioned2021-09-05T04:48:55Z-
dc.date.available2021-09-05T04:48:55Z-
dc.date.issued2020-
dc.identifier.urihttp://hdl.handle.net/20.500.12390/2647-
dc.description.abstractTo 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.es
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherSciTePresses_PE
dc.relation.ispartofVISIGRAPP 2020 - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applicationses
dc.rightsinfo:eu-repo/semantics/closedAccesses
dc.subjectAmbient Imageses_PE
dc.subjectAttention Mapes_PE
dc.subjectFlash Imageses_PE
dc.subjectGenerative Adversarial Networkses_PE
dc.subjectIlluminationes_PE
dc.titleAmbient lighting generation for flash images with guided conditional adversarial networkses
dc.typeinfo:eu-repo/semantics/articlees
dc.identifier.scopus2-s2.0-85083578185-
dc.relation.isFundedByCONV-000234-2015-FONDECYT-DE - PROMOCION 1es
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
item.languageiso639-1en-
item.fulltextNo texto completo-
item.grantfulltextnone-
Colección:2.2 Estudios de maestría
Registro simplificado



Páginas vistas

9
marcado en 23-ene-2022

Google ScholarTM

Check

  • Compartir este item
  • QR Code

Los ítems de DSpace están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.