@inproceedings{kaing-etal-2025-imagetra,
    title = "{I}mage{T}ra: Real-Time Translation for Texts in Image and Video",
    author = "Kaing, Hour  and
      Mao, Jiannan  and
      Song, Haiyue  and
      Ding, Chenchen  and
      Tanaka, Hideki  and
      Utiyama, Masao",
    editor = "Liu, Xuebo  and
      Purwarianti, Ayu",
    booktitle = "Proceedings of The 14th International Joint Conference on Natural Language Processing and The 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics: System Demonstrations",
    month = dec,
    year = "2025",
    address = "Mumbai, India",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-ijcnlp-aacl/2025.ijcnlp-demo.1/",
    pages = "1--8",
    ISBN = "979-8-89176-301-2",
    abstract = "There has been a growing research interest in in-image machine translation, which involves translating texts in images from one language to another. Recent studies continue to explore pipeline-based systems due to its straightforward construction and the consistent improvement of its underlined components. However, the existing implementation for such pipeline often lack extensibility, composability, and support for real-time translation. Therefore, this work introduces \textit{}{---}an open-source toolkit designed to facilitate the development of the pipeline-based system of in-image machine translation. The toolkit integrates state-of-the-art open-source models and tools, and is designed with a focus on modularity and efficiency, making it particularly well-suited for real-time translation. The toolkit is released at https://github.com/hour/imagetra."
}