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An Interactive Image Editing System using an Uncertainty-based Confirmation Strategy

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dc.contributor.author shinagawa, seitaro
dc.contributor.author yoshino, koichiro
dc.contributor.author SEYED HOSSEIN, ALAVI
dc.contributor.author KALLIRROI, GEORGILA
dc.contributor.author DAVID, TRAUM
dc.contributor.author SAKRIANI, SAKTI
dc.contributor.author Nakamura, Satoshi
dc.date.accessioned 2020-06-02T07:32:20Z
dc.date.available 2020-06-02T07:32:20Z
dc.date.issued 2020-03-25
dc.identifier.issn 2169-3536
dc.identifier.uri http://hdl.handle.net/10061/13987
dc.description.abstract We propose an interactive image editing system that has a confirmation dialogue strategy using an entropy-based uncertainty calculation on its generated images with Deep Convolutional Generative Adversarial Networks (DCGAN). DCGAN is an image generative model that learns an image manifold of a given dataset and enables continuous change of an image. Our proposed image editing system combines DCGAN with a natural language interface that accepts image editing requests in natural language. Although such a system is helpful for human users, it often faces uncertain requests to generate acceptable images. A promising approach to solve this problem is introducing a dialogue process that shows multiple candidates and confirms the user’s intention. However, confirming every editing request creates redundant dialogues. To achieve more efficient dialogues, we propose an entropy-based dialogue strategy that decides when the system should confirm, and enables effective image editing through a dialogue that reduces redundant confirmations. We conducted image editing dialogue experiments using an avatar face illustration dataset for editing by natural language requests. Through quantitative and qualitative analysis, our results show that our entropy-based confirmation strategy achieved an effective dialogue by generating images desired by users. ja_JP
dc.language.iso en ja_JP
dc.publisher IEEE ja_JP
dc.relation.isreplacedby https://ieeexplore.ieee.org/document/9099288/authors#authors ja_JP
dc.rights Creative Commons Attribution 4.0 License. ja_JP
dc.subject Natural languages ja_JP
dc.subject Generators ja_JP
dc.subject Generative adversarial networks ja_JP
dc.subject Task analysis ja_JP
dc.subject Training ja_JP
dc.subject Hair ja_JP
dc.subject Image generation ja_JP
dc.title An Interactive Image Editing System using an Uncertainty-based Confirmation Strategy ja_JP
dc.type.nii Journal Article ja_JP
dc.contributor.transcription シナガワ, セイタロウ
dc.contributor.transcription ヨシノ, コウイチロウ
dc.contributor.transcription ナカムラ, サトシ
dc.contributor.alternative 品川, 政太朗
dc.contributor.alternative 吉野, 幸一郎
dc.contributor.alternative 中村, 哲
dc.textversion none ja_JP
dc.identifier.jtitle IEEE Access ja_JP
dc.relation.doi 10.1109/ACCESS.2020.2997012 ja_JP
dc.identifier.NAIST-ID 84366442 ja_JP
dc.identifier.NAIST-ID 74651712 ja_JP
dc.identifier.NAIST-ID 73297715 ja_JP
dc.identifier.NAIST-ID 73296626 ja_JP


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