From panels to prose: generating literary narratives from comics

Conference item

Comics have long been a popular form of storytelling, offering visually engaging narratives that captivate audiences worldwide. However, the visual nature of comics presents a significant barrier for visually impaired readers, limiting their access to these engaging stories. In this work, we provide a pragmatic solution to this accessibility challenge by developing an automated system that generates literary1 narratives from manga comics. Our approach aims to create an evocative and immersive prose that not only conveys the original narrative but also captures the depth and complexity of characters, their interactions, and the vivid settings in which they reside. To this end we make the following contributions: (1) We present a unified model, Magiv3, that excels at various functional tasks pertaining to comic understanding, such as localising panels, characters, texts, and speech-bubble tails, performing OCR, grounding characters etc. (2) We release human-annotated captions for over 3300 Japanese comic panels, along with character grounding annotations, and benchmark large vision-language models in their ability to understand comic images. (3) Finally, we demonstrate how integrating large vision-language models with Magiv3, can generate seamless literary narratives that allows visually impaired audiences to engage with the depth and richness of comic storytelling.

Authors: Sachdeva, R; Zisserman, A

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: IEEE
• Host title: 2025 IEEE/CVF International Conference on Computer Vision (ICCV)
• Pages: 21864-21873
• Publication date: 2026-04-29
• Acceptance date: 2025-07-23
• Event title: International Conference on Computer Vision (ICCV 2025)
• Event location: Honolulu, Hawai'i, USA
• Event website: https://www.robots.ox.ac.uk/~vgg/publications/2025/Sachdeva25/sachdeva25.pdf
• Event start date: 2025-10-19
• Event end date: 2025-10-23
• DOI: 10.1109/ICCV51701.2025.02030
• EISSN: 2380-7504
• ISSN: 1550-5499
• EISBN: 9788331587758
• ISBN: 9798331587765
• Language: English
• Keywords: feeds; antennas; protocols; HTTP; internet; instant messaging; radio access networks; regional area networks; videos; communication systems