@inproceedings{mansimov-etal-2020-towards,
title = "Towards End-to-End In-Image Neural Machine Translation",
author = "Mansimov, Elman and
Stern, Mitchell and
Chen, Mia and
Firat, Orhan and
Uszkoreit, Jakob and
Jain, Puneet",
editor = "Castellucci, Giuseppe and
Filice, Simone and
Poria, Soujanya and
Cambria, Erik and
Specia, Lucia",
booktitle = "Proceedings of the First International Workshop on Natural Language Processing Beyond Text",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.nlpbt-1.8",
doi = "10.18653/v1/2020.nlpbt-1.8",
pages = "70--74",
abstract = "In this paper, we offer a preliminary investigation into the task of in-image machine translation: transforming an image containing text in one language into an image containing the same text in another language. We propose an end-to-end neural model for this task inspired by recent approaches to neural machine translation, and demonstrate promising initial results based purely on pixel-level supervision. We then offer a quantitative and qualitative evaluation of our system outputs and discuss some common failure modes. Finally, we conclude with directions for future work.",
}
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%0 Conference Proceedings
%T Towards End-to-End In-Image Neural Machine Translation
%A Mansimov, Elman
%A Stern, Mitchell
%A Chen, Mia
%A Firat, Orhan
%A Uszkoreit, Jakob
%A Jain, Puneet
%Y Castellucci, Giuseppe
%Y Filice, Simone
%Y Poria, Soujanya
%Y Cambria, Erik
%Y Specia, Lucia
%S Proceedings of the First International Workshop on Natural Language Processing Beyond Text
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F mansimov-etal-2020-towards
%X In this paper, we offer a preliminary investigation into the task of in-image machine translation: transforming an image containing text in one language into an image containing the same text in another language. We propose an end-to-end neural model for this task inspired by recent approaches to neural machine translation, and demonstrate promising initial results based purely on pixel-level supervision. We then offer a quantitative and qualitative evaluation of our system outputs and discuss some common failure modes. Finally, we conclude with directions for future work.
%R 10.18653/v1/2020.nlpbt-1.8
%U https://aclanthology.org/2020.nlpbt-1.8
%U https://doi.org/10.18653/v1/2020.nlpbt-1.8
%P 70-74
Markdown (Informal)
[Towards End-to-End In-Image Neural Machine Translation](https://aclanthology.org/2020.nlpbt-1.8) (Mansimov et al., nlpbt 2020)
ACL
- Elman Mansimov, Mitchell Stern, Mia Chen, Orhan Firat, Jakob Uszkoreit, and Puneet Jain. 2020. Towards End-to-End In-Image Neural Machine Translation. In Proceedings of the First International Workshop on Natural Language Processing Beyond Text, pages 70–74, Online. Association for Computational Linguistics.