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DC poleHodnotaJazyk
dc.contributor.authorKim, Jihwan
dc.contributor.authorChoi, Sunghee
dc.contributor.editorSkala, Václav
dc.date.accessioned2020-07-24T06:41:57Z-
dc.date.available2020-07-24T06:41:57Z-
dc.date.issued2020
dc.identifier.citationJournal of WSCG. 2020, vol. 28, no. 1-2, p. 57-63en
dc.identifier.issn1213-6972 (print)
dc.identifier.issn1213-6980 (CD-ROM)
dc.identifier.issn1213-6964 (on-line)
dc.identifier.urihttp://wscg.zcu.cz/WSCG2020/2020-J_WSCG-1-2.pdf
dc.identifier.urihttp://hdl.handle.net/11025/38425
dc.format7 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesJournal of WSCGen
dc.rights© Václav Skala - UNION Agencycs
dc.subjecthalucinace obličejecs
dc.subjectpotrubní síťcs
dc.subjectvěkcs
dc.subjectosobnostcs
dc.subjecthluboké učenícs
dc.titleHallucinating Very Low Resolution Face Images to 16x magnification with Age based Attributesen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedFace hallucination is a type of super resolution that restores very low resolution (8 8 pixel) to high resolution (128 128 pixel) face images. Since unique facial features caused by age, e.g.wrinkles, are ignored during restoration, restored face images can be somewhat dissimilar to the original faces, particularly for older people. To solve this problem, we construct a pipeline network to restore face images more realistically by including age attribute, predicted from the low resolution image. Predicted age attribute is divided into young and old groups, where the aging network is the last pipeline stage and only applied when the original face image includes old age attributes. Thus, older people tend to be restored with wrinkles and features similar to their original appearance. Restored images are compared qualitatively and quantitatively with images created by existing methods. We show that the proposed method maintains and restores age related personality features, such as wrinkles, producing higher structural similarity index than other methods.en
dc.subject.translatedface hallucinationen
dc.subject.translatedpipeline networken
dc.subject.translatedageen
dc.subject.translatedpersonalityen
dc.subject.translateddeep learningen
dc.identifier.doihttps://doi.org/10.24132/JWSCG.2020.28.7
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:Volume 28, Number 1-2 (2020)

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Použijte tento identifikátor k citaci nebo jako odkaz na tento záznam: http://hdl.handle.net/11025/38425

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  1. DSpace at University of West Bohemia
  2. Publikace ZČU / UWB Publications
  3. Časopisy ZČU / UWB Journals
  4. Journal of WSCG
  5. Volume 28 (2020)
  6. Volume 28, Number 1-2 (2020)