Scene Text Editing (STE) is a challenging research problem, and it aims to modify existing texts in an image while preserving the background and the font style of the original text of the image. Due to its various real-life applications, researchers have explored several approaches toward STE in recent years. However, most of the existing STE methods show inferior editing performance because of (1) complex image backgrounds, (2) various font styles, and (3) varying word lengths within the text. To address such inferior editing performance issues, in this paper, we propose a novel font-agnostic scene text editing framework, named FAST, for simultaneously generating text in arbitrary styles and locations while preserving a natural and realistic appearance through combined mask generation and style transfer. The proposed approach differs from the existing methods as they directly modify all image pixels. Instead, the proposed method has introduced a filtering mechanism to remove background distractions, allowing the network to focus solely on the text regions where editing is required. Additionally, a text-style transfer module has been designed to mitigate the challenges posed by varying word lengths. Extensive experiments and ablations have been conducted, and the results demonstrate that the proposed method outperforms the existing methods both qualitatively and quantitatively.

本文提出了一种名为FAST的新颖无字体场景文本编辑框架，用于在保留自然和逼真外观的同时，同时在任意样式和位置生成文本，通过结合遮罩生成和样式转移。通过滤波机制去除背景干扰，使网络仅集中于需要编辑的文本区域，同时设计了文本样式转移模块以减轻不同字长度带来的挑战，实验证明该方法在质量和数量上优于现有方法。

FAST：面向字体无关的场景文本编辑