license:mit region:us
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license: mit
---

# ICDAR 2025 Competition on End-to-end Document Image Machine Translation (OCR-free Track)

This is the official repository for [***ICDAR 2025 Competition on End-to-end Document Image Machine Translation (OCR-free Track)***](https://cip-documentai.github.io/)

## For Participants  
Participants are required to translate all the images in the **competition_testset_images.zip** using an end-to-end OCR-free method into Simplified Chinese (zh-CN), and fill in **answer.json** file.
The file should be zipped and submitted to Codalab.  
In **answer.json** file, the **key** corresponds to the image file name, and the **value** is the translation of each image as a single string (str) after [**jieba**](https://github.com/fxsjy/jieba) cut.

## Training Dataset Download
The dataset can be downloaded from this [huggingface link](https://huggingface.co/datasets/liangyupu/DoTA_dataset).

## Baseline Implementation
This is an implementation of a simple end-to-end document image machine translation model with an image encoder and a translation decoder.
Details can be found in [***Document Image Machine Translation with Dynamic Multi-pre-trained Models Assembling (NAACL 2024 Main)***](https://aclanthology.org/2024.naacl-long.392/) Section 5.3 Base.



