yztian/MTedIIMT

PRIM: Towards Practical In-Image Multilingual Machine Translation (EMNLP 2025 Main)

📄Paper arXiv | 💻Code GitHub | 🤗Benchmark HuggingFace | 🤗Model HuggingFace

Introduction

This repository provides the MTedIIMT training set, which is introduced in our paper PRIM: Towards Practical In-Image Multilingual Machine Translation.

The text in the source and target images is derived from MTed [1], while the background images are captured from Ted and rendered using the TRDG toolkit [2]. We sincerely thank the authors of these works for their valuable contributions.

Extraction

Each language-pair directory (e.g., ./en-de) contains multiple compressed parts (.part-aa, .part-ab, …) along with a checksum file (SHA256SUMS.txt).

The split parts must be concatenated back into a single .tar.gz archive before extraction. You can do this in one step:

cd ./en-de
cat MTedIIMT_subset_en_de_lmdb.tar.gz.part-* | tar -xzf - -C /path/to/dest

• part-* expands to all split files in order (aa, ab, ac, …).

• Use -C /path/to/dest to specify the target extraction directory (create it beforehand).

Citation

If you find our work helpful, we would greatly appreciate it if you could cite our paper:

@misc{tian2025primpracticalinimagemultilingual,
      title={PRIM: Towards Practical In-Image Multilingual Machine Translation}, 
      author={Yanzhi Tian and Zeming Liu and Zhengyang Liu and Chong Feng and Xin Li and Heyan Huang and Yuhang Guo},
      year={2025},
      eprint={2509.05146},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2509.05146}, 
}

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[1] The multitarget ted talks task. http://www.cs.jhu.edu/~kevinduh/a/multitarget-tedtalks/

[2] https://github.com/Belval/TextRecognitionDataGenerator