FlowTranslator: Training-Free In-Image Machine Translation with Flow-Based Editing
FlowTranslator is a training-free framework for in-image machine translation that replaces text in images with translations while preserving visual context.
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- Primary sourceHugging Face
- Discovery linkHugging Face
- Linked in sourceView arXiv page
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FlowTranslator is a training-free framework for in-image machine translation that replaces text in images with translations while preserving visual context. It uses an OCR model and an LLM to generate a translation prompt, injected into a text-to-image diffusion model, with two trajectory controls, Region Coupling Release and Coupling Expansion, to improve translated text generation. Under the EasyOCR read-back protocol it reports average PRIM BLEU of 20.6 and COMET of 57.2, outperforming the training-based UniTranslator baseline. On whole-image ScenePair photographs translated into Chinese, it reports 40.1% exact-match accuracy.
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Source claims not independently checked; results are reported under a specific EasyOCR read-back evaluation protocol.
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Uses an OCR model and an LLM to generate a translation prompt injected into a T2I diffusion model.
Source: Hugging Face ↗Stored source-based brief · key point 1 · AINewsIQ paraphraseRegion Coupling Release partially decorrelates target-branch noise inside the text region early in the trajectory.
Source: Hugging Face ↗Stored source-based brief · key point 2 · AINewsIQ paraphraseReports average PRIM BLEU 20.6 and COMET 57.2 under the EasyOCR read-back protocol, above UniTranslator.
Source: Hugging Face ↗Stored source-based brief · key point 3 · AINewsIQ paraphraseLimits from the stored brief
Source claims not independently checked; results are reported under a specific EasyOCR read-back evaluation protocol.
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Why this may matter
The work proposes that multilingual text-generation ability in text-to-image models can be repurposed for in-image translation without paired training images, lowering data requirements for this task.
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