Recursive Chaining of Reversible Image-to-Image Translators for Face Aging

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorHeljakka, Arien_US
dc.contributor.authorSolin, Arnoen_US
dc.contributor.authorKannala, Juhoen_US
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.contributor.departmentProfessorship Solin A.en_US
dc.date.accessioned2019-01-14T09:25:10Z
dc.date.available2019-01-14T09:25:10Z
dc.date.issued2018-01-01en_US
dc.description.abstractThis paper addresses the modeling and simulation of progressive changes over time, such as human face aging. By treating the age phases as a sequence of image domains, we construct a chain of transformers that map images from one age domain to the next. Leveraging recent adversarial image translation methods, our approach requires no training samples of the same individual at different ages. Here, the model must be flexible enough to translate a child face to a young adult, and all the way through the adulthood to old age. We find that some transformers in the chain can be recursively applied on their own output to cover multiple phases, compressing the chain. The structure of the chain also unearths information about the underlying physical process. We demonstrate the performance of our method with precise and intuitive metrics, and visually match with the face aging state-of-the-art.en
dc.description.versionPeer revieweden
dc.format.extent12
dc.format.extent309-320
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationHeljakka , A , Solin , A & Kannala , J 2018 , Recursive Chaining of Reversible Image-to-Image Translators for Face Aging . in Advanced Concepts for Intelligent Vision Systems - 19th International Conference, ACIVS 2018, Proceedings . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , vol. 11182 LNCS , Springer , pp. 309-320 , International Conference on Advanced Concepts for Intelligent Vision Systems , Poitiers , France , 24/09/2018 . https://doi.org/10.1007/978-3-030-01449-0_26en
dc.identifier.doi10.1007/978-3-030-01449-0_26en_US
dc.identifier.isbn9783030014483
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.otherPURE UUID: e56fb989-7b55-4c4f-995c-995457321bb4en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/e56fb989-7b55-4c4f-995c-995457321bb4en_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85054807571&partnerID=8YFLogxKen_US
dc.identifier.otherPURE LINK: https://arxiv.org/abs/1802.05023en_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/42971641/1802.05023.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/36037
dc.identifier.urnURN:NBN:fi:aalto-201901141220
dc.language.isoenen
dc.publisherSpringer
dc.relation.ispartofInternational Conference on Advanced Concepts for Intelligent Vision Systemsen
dc.relation.ispartofseriesAdvanced Concepts for Intelligent Vision Systems - 19th International Conference, ACIVS 2018, Proceedingsen
dc.relation.ispartofseriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en
dc.relation.ispartofseriesVolume 11182 LNCSen
dc.rightsopenAccessen
dc.subject.keywordDeep learningen_US
dc.subject.keywordFace agingen_US
dc.subject.keywordFace synthesisen_US
dc.subject.keywordGANen_US
dc.subject.keywordTransfer learningen_US
dc.titleRecursive Chaining of Reversible Image-to-Image Translators for Face Agingen
dc.typeConference article in proceedingsfi
dc.type.versionacceptedVersion
Files