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English(EN) FlowTranslator: Training-Free In-Image Machine Translation with Flow-Based Editing

FlowTranslator 利用扩散模型提供无需训练的图像内翻译

研究人员开发了 FlowTranslator,一种新颖的图像内机器翻译 (IIMT) 框架,该框架不需要配对的训练数据。该方法利用先进的文本到图像扩散模型,首先使用 OCR 和 LLM 生成翻译提示。该框架引入了两种轨迹控制:区域耦合释放 (RCR) 和耦合扩展 (CE),以提高图像内翻译文本的准确性和自然度。FlowTranslator 在 PRIM BLEU 和 COMET 等基准测试中表现优于现有的基于训练的方法,并在真实的 ScenePair 照片上取得了良好效果。 AI

影响 引入了一种无需训练的图像内翻译方法,有可能降低此类任务的数据需求和计算成本。

排序理由 该集群描述了一篇详细介绍图像内机器翻译新方法的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 Hugging Face Daily Papers 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

FlowTranslator 利用扩散模型提供无需训练的图像内翻译

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该集群描述了一篇详细介绍图像内机器翻译新方法的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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完整方法见我们的编辑标准。

报道来源 [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    FlowTranslator:无需训练的基于流的编辑的图像内机器翻译

    In-image machine translation (IIMT) replaces text in an image with its translation while preserving the surrounding visual context. Existing task-specific models achieve convincing performance but require massive paired training images before and after translation. As advanced te…