FAST: Font-Agnostic Scene Text Editing
Alloy Das Prasun Roy Saumik Bhattacharya Subhankar Ghosh Umapada Pal Michael Blumenstein
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.