Facial Feature Based Image-to-Image Translation Method
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 강신진 | - |
dc.date.available | 2021-03-17T06:59:29Z | - |
dc.date.created | 2021-02-26 | - |
dc.date.issued | 2020-12 | - |
dc.identifier.issn | 1976-7277 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/11991 | - |
dc.description.abstract | The recent expansion of the digital content market is increasing the technical demand for various facial image transformations within the virtual environment. The recent image translation technology enables changes between various domains. However, current image-to-image translation techniques do not provide stable performance through unsupervised learning, especially for shape learning in the face transition field. This is because the face is a highly sensitive feature, and the quality of the resulting image is significantly affected, especially if the transitions in the eyes, nose, and mouth are not effectively performed. We herein propose a new unsupervised method that can transform an in-wild face image into another face style through radical transformation. Specifically, the proposed method applies two face-specific feature loss functions for a generative adversarial network. The proposed technique shows that stable domain conversion to other domains is possible while maintaining the image characteristics in the eyes, nose, and mouth. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | 한국인터넷정보학회 | - |
dc.title | Facial Feature Based Image-to-Image Translation Method | - |
dc.title.alternative | Facial Feature Based Image-to-Image Translation Method | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | 강신진 | - |
dc.identifier.doi | 10.3837/tiis.2020.12.012 | - |
dc.identifier.scopusid | 2-s2.0-85099459531 | - |
dc.identifier.wosid | 000605575100012 | - |
dc.identifier.bibliographicCitation | KSII Transactions on Internet and Information Systems, v.14, no.12, pp.4835 - 4848 | - |
dc.relation.isPartOf | KSII Transactions on Internet and Information Systems | - |
dc.citation.title | KSII Transactions on Internet and Information Systems | - |
dc.citation.volume | 14 | - |
dc.citation.number | 12 | - |
dc.citation.startPage | 4835 | - |
dc.citation.endPage | 4848 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.identifier.kciid | ART002673621 | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kci | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordAuthor | Game Character Generation | - |
dc.subject.keywordAuthor | Character Customization | - |
dc.subject.keywordAuthor | Virtual Character | - |
dc.subject.keywordAuthor | Image Translation | - |
dc.subject.keywordAuthor | Convolutional Neural Network | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
94, Wausan-ro, Mapo-gu, Seoul, 04066, Korea02-320-1314
COPYRIGHT 2020 HONGIK UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.