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Detection of Diffusion-Generated Images Using Sparse Coding
http://hdl.handle.net/10228/0002001581
http://hdl.handle.net/10228/000200158133f44b3a-446a-41b0-95fd-302b9c75298a
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10450309.pdf (233.2 KB)
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| アイテムタイプ | 共通アイテムタイプ(1) | |||||||||||
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| 公開日 | 2025-04-14 | |||||||||||
| タイトル | ||||||||||||
| タイトル | Detection of Diffusion-Generated Images Using Sparse Coding | |||||||||||
| 言語 | en | |||||||||||
| 著者 |
Tanaka, Daishi
× Tanaka, Daishi
× 新見, 道治
WEKO
944
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| 著作権関連情報 | ||||||||||||
| 権利情報 | Copyright (c) 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |||||||||||
| 言語 | en | |||||||||||
| 抄録 | ||||||||||||
| 内容記述タイプ | Abstract | |||||||||||
| 内容記述 | This paper proposes a method for detecting images generated by diffusion models using sparse coding. In the diffusion model, an image can be generated by removing noise from a noisy image. This different generation process from real images leads us to believe that there may be a statistical difference in pixels between the real and the generated images. Specifically, the image is divided into small patch regions, and all patch images are reconstructed using the basis image. In this process, sparse coefficients that contain many zeros are obtained using sparse coding, and features are calculated from the obtained coefficients. Then, a simple discriminator using the features as input is trained with a small number of data to discriminate the diffusion-generated images. In our experiments, we evaluated the proposed method on six datasets created using three diffusion models and two real image datasets. Experiments were also conducted to evaluate the robustness of the proposed method against JPEG compression. Experimental results show that our proposed method is sufficiently robust against JPEG compression with as few as 1800 training data. | |||||||||||
| 言語 | en | |||||||||||
| 備考 | ||||||||||||
| 内容記述タイプ | Other | |||||||||||
| 内容記述 | 2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 03-06 December 2024, Macau, Macao | |||||||||||
| 言語 | en | |||||||||||
| 書誌情報 |
en : 2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) 発行日 2025-01-27 |
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| 出版社 | ||||||||||||
| 出版者 | IEEE | |||||||||||
| 言語 | ||||||||||||
| 言語 | eng | |||||||||||
| 資源タイプ | ||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||
| 資源タイプ | journal article | |||||||||||
| 出版タイプ | ||||||||||||
| 出版タイプ | AM | |||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||||||||
| DOI | ||||||||||||
| 識別子タイプ | DOI | |||||||||||
| 関連識別子 | https://doi.org/10.1109/APSIPAASC63619.2025.10848756 | |||||||||||
| ISBN | ||||||||||||
| 識別子タイプ | ISBN | |||||||||||
| 関連識別子 | 979-8-3503-6733-1 | |||||||||||
| ISSN | ||||||||||||
| 収録物識別子タイプ | EISSN | |||||||||||
| 収録物識別子 | 2640-0103 | |||||||||||
| 会議記述 | ||||||||||||
| 会議名 | 2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) | |||||||||||
| 言語 | en | |||||||||||
| 開始年 | 2024 | |||||||||||
| 開始月 | 12 | |||||||||||
| 開始日 | 03 | |||||||||||
| 終了年 | 2024 | |||||||||||
| 終了月 | 12 | |||||||||||
| 終了日 | 06 | |||||||||||
| 開催国 | CHN | |||||||||||
| 査読の有無 | ||||||||||||
| 値 | yes | |||||||||||
| 研究者情報 | ||||||||||||
| URL | https://hyokadb02.jimu.kyutech.ac.jp/html/236_ja.html | |||||||||||
| 論文ID（連携） | ||||||||||||
| 値 | 10450309 | |||||||||||
| 連携ID | ||||||||||||
| 値 | 14292 | |||||||||||
