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dc.contributor.authorKınlı, Osman Furkan
dc.contributor.authorÖzcan, Barış
dc.contributor.authorKıraç, Mustafa Furkan
dc.date.accessioned2021-06-23T09:31:40Z
dc.date.available2021-06-23T09:31:40Z
dc.date.issued2020-04-14
dc.identifier.isbn978-145037749-2
dc.identifier.urihttp://hdl.handle.net/10679/7447
dc.identifier.urihttps://dl.acm.org/doi/abs/10.1145/3397125.3397155
dc.description.abstractInpainting a particular missing region in an image is a challenging vision task, and promising improvements on this task have been achieved with the help of the recent developments in vision-related deep learning studies. Although it may have a direct impact on the decisions of AI-based fashion analysis systems, a limited number of studies for image inpainting have been done in fashion domain, so far. In this study, we propose a multi-modal generative deep learning approach for filling the missing parts in fashion images by constraining visual features with textual features extracted from image descriptions. Our model is composed of four main blocks which can be introduced as textual feature extractor, coarse image generator guided by textual features, fine image generator enhancing the coarse output, and lastly global and local discriminators improving refined outputs. Several experiments conducted on FashionGen dataset with different combination of neural network components show that our multi-modal approach is able to generate visually plausible patches to fill the missing parts in the images.en_US
dc.language.isoengen_US
dc.publisherThe ACM Digital Libraryen_US
dc.relation.ispartofICCTA '20: Proceedings of the 2020 6th International Conference on Computer and Technology Applications
dc.rightsrestrictedAccess
dc.titleDescription-aware fashion image inpainting with convolutional neural networks in coarse-to-fine manneren_US
dc.typeConference paperen_US
dc.publicationstatusPublisheden_US
dc.contributor.departmentÖzyeğin University
dc.contributor.authorID(ORCID 0000-0002-9192-6583 & YÖK ID 283852) Kınlı, Furkan
dc.contributor.authorID(ORCID 0000-0001-9177-0489 & YÖK ID 124619) Kıraç, Furkan
dc.contributor.ozuauthorKınlı, Osman Furkan
dc.contributor.ozuauthorKıraç, Mustafa Furkan
dc.identifier.startpage74en_US
dc.identifier.endpage79en_US
dc.identifier.doi10.1145/3397125.3397155en_US
dc.subject.keywordsDeep learningen_US
dc.subject.keywordsFashion analysisen_US
dc.subject.keywordsGenerative learningen_US
dc.subject.keywordsImage inpaintingen_US
dc.subject.keywordsImage reconstructionen_US
dc.subject.keywordsMulti-modal neural networksen_US
dc.identifier.scopusSCOPUS:2-s2.0-85086180951
dc.contributor.ozugradstudentÖzcan, Barış
dc.contributor.authorMale3
dc.relation.publicationcategoryConference Paper - International - Institutional Academic Staff and PhD Student


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