Work

AnyTrans: Translate AnyText in the Image with Large Scale Models

Year: 2024

Type: conference-paper

Abstract: This paper introduces AnyTrans, an allencompassing framework for the task-In-Image Machine Translation (IIMT), which includes multilingual text translation and text fusion within images.Our framework leverages the strengths of large-scale models, such as Large Language Models (LLMs) and textguided diffusion models, to incorporate contextual cues from both textual and visual elements during translation.The few-shot learning capability of LLMs allows for the translation of fragmented texts by considering the overall context.Meanwhile, diffusion models' advanced inpainting and editing abilities make it possible to fuse translated text seamlessly into the original image while preserving its style and realism.Our framework can be constructed entirely using open-source models and requires no training, making it highly accessible and easily expandable.To encourage advancement in the IIMT task, we have meticulously compiled a test dataset called MTIT6, which consists of multilingual text image translation data from six language pairs.

Source: Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP)

DOI: 10.18653/v1/2024.findings-emnlp.137