{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229216","sets":["1164:6757:11095:11361"]},"path":["11361"],"owner":"44499","recid":"229216","title":["チャネルアテンションと行列積アテンションによる顔画像生成敵対的学習ネットワーク"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-11-09"},"_buckets":{"deposit":"c238b693-4557-4514-b623-f5d01ac375bb"},"_deposit":{"id":"229216","pid":{"type":"depid","value":"229216","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"チャネルアテンションと行列積アテンションによる顔画像生成敵対的学習ネットワーク","author_link":["616004","616005","616003"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"チャネルアテンションと行列積アテンションによる顔画像生成敵対的学習ネットワーク"}]},"item_type_id":"4","publish_date":"2023-11-09","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"慶應義塾大学理工学部"},{"subitem_text_value":"慶應義塾大学理工学部"},{"subitem_text_value":"慶應義塾大学理工学部"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/229216/files/IPSJ-DCC23035049.pdf","label":"IPSJ-DCC23035049.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DCC23035049.pdf","filesize":[{"value":"1.9 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"50"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"93e62e24-5ece-4dbc-995e-8c5f7b2787f1","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"小倉, 英敏"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"池原, 雅章"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"江角, 真也"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12628338","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8868","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"顔写真から顔スケッチを生成するタスクは，畳み込みニューラルネットワーク (CNN) や Vision Transformer (ViT) をベースとした敵対的生成ネットワーク (GAN）により発展した．CNN では局所性により画像や輪郭がぼやけた画像が生成される．また ViT は大域的情報を捉えることを得意とするが局所的特徴量を捉える点では CNN に及ばず，輪郭などの線のぼやけを防げるものの細かなテクスチャが反映されにくい．そこでチャネルの重みを機能的に調整する Channel Attention と，行列積によって求められる画像の縦横の類似度をもとにピクセルに重み付けする行列積アテンション (Matrix Product Attention : MP Attention) を CNN に組み込むことで局所的特徴と広域な特徴の双方を捉えた顔画像のイラスト生成モデル，Face drawing GAN を提案する．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告デジタルコンテンツクリエーション（DCC）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2023-11-09","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"49","bibliographicVolumeNumber":"2023-DCC-35"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":229216,"updated":"2025-01-19T11:35:54.836919+00:00","links":{},"created":"2025-01-19T01:28:20.156451+00:00"}