Manga109-v2026: Revisiting Manga109 Annotations for Modern Manga Understanding
Manga is a culturally distinctive multimodal medium and one of the most influential forms of Japanese popular culture. As AI systems increasingly target manga understanding, OCR, and translation, Manga109 has become a foundational dataset for manga-related AI research. However, the current Manga109 dataset contains inaccurate transcriptions and coarse annotations, which do not align well with modern OCR and multimodal manga understanding tasks. In this work, we revisit the dialogue text annotations of Manga109 and identify five categories of annotation issues, including inaccurate transcriptions, missing text regions, overlapping dialogue and onomatopoeia, and under-segmented speech ballo...
| Authors | Jeonghun Baek, Atsuyuki Miyai, Shota Onohara et al. |
|---|---|
| Primary category | cs.CL |
| Published | 20 May 2026 |
| Last updated at source | 12 June 2026 |
Connected in the knowledge graph
- hal-utokyo/Manga109Dataset · cited by
- hal-utokyo/Manga109-sDataset · cited by
Models and datasets referencing this paper
- hal-utokyo/Manga109-sDataset
- hal-utokyo/Manga109Dataset
Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.