@inproceedings{gonzalez-etal-2026-image,
    title = "In-Image Machine Translation. A Preliminary Modular Approach",
    author = "Gonzalez, Sergio Gomez  and
      Domingo, Miguel  and
      Casacuberta, Francisco",
    editor = "Baez Santamaria, Selene  and
      Somayajula, Sai Ashish  and
      Yamaguchi, Atsuki",
    booktitle = "Proceedings of the 19th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 4: Student Research Workshop)",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-eacl/2026.eacl-srw.38/",
    pages = "502--513",
    ISBN = "979-8-89176-383-8",
    abstract = "In-image machine translation is a sub-task of Image-Based Machine Translation that aims to substitute text embedded in images with its translation into another language. In the current work, we define a simple task with a synthetic dataset based on rendering parallel text over a plain background. Furthermore, we experiment with different optical character recognition, machine translation and image synthesis models to include in our ensemble. Then, we present our cascade approach as a pipeline that obtains the transcript of the original image, translates it, and generates a new image (image synthesis) similar to the original one. Finally, we compare the performance of our approach with several current state-of-the-art models, including an end-to-end approach, demonstrating its competitiveness."
}