Tails Tell Tales: Chapter-Wide Manga Transcriptions with Character Names
<|reference_start|>Tails Tell Tales: Chapter-Wide Manga Transcriptions with Character Names: Enabling engagement of manga by visually impaired individuals presents a significant challenge due to its inherently visual nature. With the goal of fostering accessibility, this paper aims to generate a dialogue transcript of a complete manga chapter, entirely automatically, with a particular emphasis on ensuring narrative consistency. This entails identifying (i) what is being said, i.e., detecting the texts on each page and classifying them into essential vs non-essential, and (ii) who is saying it, i.e., attributing each dialogue to its speaker, while ensuring the same characters are named consistently throughout the chapter.   To this end, we introduce: (i) Magiv2, a model that is capable of generating high-quality chapter-wide manga transcripts with named characters and significantly higher precision in speaker diarisation over prior works; (ii) an extension of the PopManga evaluation dataset, which now includes annotations for speech-bubble tail boxes, associations of text to corresponding tails, classifications of text as essential or non-essential, and the identity for each character box; and (iii) a new character bank dataset, which comprises over 11K characters from 76 manga series, featuring 11.5K exemplar character images in total, as well as a list of chapters in which they appear. The code, trained model, and both datasets can be found at: https://github.com/ragavsachdeva/magi<|reference_end|>
@article{sachdeva2024tails,
    title={Tails Tell Tales: Chapter-Wide Manga Transcriptions with Character Names},
    author={Ragav Sachdeva, Gyungin Shin, Andrew Zisserman},
    journal={arXiv preprint arXiv:2408.00298},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.00298},
    primaryClass={cs.CV}
}