Abstract
Adapting advertisements for multilingual audiences requires more than simple text translation; it demands preservation of visual consistency, spatial alignment, and stylistic integrity across diverse languages and formats. We introduce a structured framework that combines automated components with human oversight to address the complexities of advertisement localization. To the best of our knowledge, this is the first work to integrate scene text detection, inpainting, machine translation (MT), and text reimposition specifically for accelerating ad localization evaluation workflows. Qualitative results across six locales demonstrate that our approach produces semantically accurate and visually coherent localized advertisements, suitable for deployment in real-world workflows.
Abstract (translated)
将广告适应为多语言受众的需求不仅仅局限于简单的文本翻译；这还需要在多种语言和格式下保持视觉一致性、空间对齐以及风格的完整性。我们提出了一种结构化的框架，该框架结合了自动化组件与人工监督，以解决广告本地化过程中遇到的各种复杂问题。据我们所知，这是首次将场景文本检测、图像修复（inpainting）、机器翻译（MT）和文本重新置入技术结合起来，专门用于加速广告本地化评估工作流程的研究。通过六个不同地区的定性结果证明，我们的方法能够生成语义准确且视觉上连贯的本地化广告，适合应用于实际的工作环境中。
URL
https://arxiv.org/abs/2509.12543
