Editing raster text is a promising but challenging task. We propose to apply text vectorization for the task of raster text editing in display media, such as posters, web pages, or advertisements. In our approach, instead of applying image transformation or generation in the raster domain, we learn a text vectorization model to parse all the rendering parameters including text, location, size, font, style, effects, and hidden background, then utilize those parameters for reconstruction and any editing task. Our text vectorization takes advantage of differentiable text rendering to accurately reproduce the input raster text in a resolution-free parametric format. We show in the experiments that our approach can successfully parse text, styling, and background information in the unified model, and produces artifact-free text editing compared to a raster baseline.

翻译：编辑光栅文本是一项充满希望但具有挑战性的任务。 我们提议在展示媒体,如海报、网页或广告中应用文本矢量化来完成光栅文本编辑任务。 我们的方法不是在光栅域内应用图像转换或生成,而是学习一个文本矢量化模型来分析包括文字、位置、大小、字体、风格、效果和隐藏背景在内的所有构建参数,然后利用这些参数来重建或编辑任务。 我们的文本矢量化利用不同的文本来准确复制无分辨率参数格式的输入光栅文本。 我们在实验中显示,我们的方法可以成功地分析统一模型中的文本、条纹和背景资料,并制作与光栅基线相比的无产物文本编辑。