Building a Manga Dataset “Manga109” With Annotations for Multimedia Applications
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- Kiyoharu Aizawa
- The University of Tokyo
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- Azuma Fujimoto
- The University of Tokyo
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- Atsushi Otsubo
- The University of Tokyo
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- Toru Ogawa
- The University of Tokyo
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- Yusuke Matsui
- The University of Tokyo
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- Koki Tsubota
- The University of Tokyo
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- Hikaru Ikuta
- The University of Tokyo
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説明
Manga, or comics, which are a type of multimodal artwork, have been left behind in the recent trend of deep learning applications because of the lack of a proper dataset. Hence, we built Manga109, a dataset consisting of a variety of 109 Japanese comic books (94 authors and 21,142 pages) and made it publicly available by obtaining author permissions for academic use. We carefully annotated the frames, speech texts, character faces, and character bodies; the total number of annotations exceeds 500k. This dataset provides numerous manga images and annotations, which will be beneficial for use in machine learning algorithms and their evaluation. In addition to academic use, we obtained further permission for a subset of the dataset for industrial use. In this article, we describe the details of the dataset and present a few examples of multimedia processing applications (detection, retrieval, and generation) that apply existing deep learning methods and are made possible by the dataset.
10 pages, 8 figures
収録刊行物
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- IEEE MultiMedia
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IEEE MultiMedia 27 (2), 8-18, 2020-04-01
Institute of Electrical and Electronics Engineers (IEEE)
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キーワード
詳細情報 詳細情報について
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- CRID
- 1361137045657200256
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- ISSN
- 19410166
- 1070986X
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- データソース種別
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- Crossref
- OpenAIRE