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English(EN) Diffusion-Based Ukrainian Handwritten Text Generation with Cross-Domain Style Transfer

扩散模型生成乌克兰手写文本,创建新数据集

研究人员开发了一种使用扩散模型生成乌克兰手写文本的方法,解决了低资源书写系统中的空白。他们创建了一个包含来自308位作者的超过126,000个乌克兰手写单词的新数据集。最初在拉丁字母脚本上训练的DiffusionPen模型,在该数据集上进行了重新训练,并展示了有效的跨域风格迁移能力,能够泛化到历史和当代乌克兰手写体。 AI

影响 将风格化手写文本生成能力扩展到代表性不足的西里尔字母脚本,可能为历史文献分析和数字归档带来新应用。

排序理由 关于新数据集和模型改编以用于手写文本生成的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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

扩散模型生成乌克兰手写文本,创建新数据集

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关于新数据集和模型改编以用于手写文本生成的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Andrii Ahitoliev, Pavlo Berezin ·

    基于扩散模型的乌克兰手写文本生成及跨域风格迁移

    arXiv:2605.27487v1 Announce Type: cross Abstract: Handwritten text generation (HTG) conditioned on writer style has been widely studied for Latin scripts, but remains underexplored for low-resource and non-Latin writing systems, leaving open how well existing models generalise be…