TextMaster: A Unified Framework for Realistic Text Editing via Glyph-Style Dual-Control

TL;DR

TextMaster is a novel framework that improves realistic text editing in images by combining high-resolution glyph information, attention-based layout control, and style transfer techniques, achieving state-of-the-art results.

Contribution

The paper introduces a unified approach that enhances text editing accuracy, controllability, and style transfer in images, addressing limitations of previous methods.

Findings

Achieves high accuracy in complex text editing scenarios.

Demonstrates superior style controllability in text rendering.

Outperforms existing methods in quality and fidelity.

Abstract

In image editing tasks, high-quality text editing capabilities can significantly reduce both human and material resource costs. Existing methods, however, face significant limitations in terms of stroke accuracy for complex text and controllability of generated text styles. To address these challenges, we propose TextMaster, a solution capable of accurately editing text across various scenarios and image regions, while ensuring proper layout and controllable text style. Our method enhances the accuracy and fidelity of text rendering by incorporating high-resolution standard glyph information and applying perceptual loss within the text editing region. Additionally, we leverage an attention mechanism to compute intermediate layer bounding box regression loss for each character, enabling the model to learn text layout across varying contexts. Furthermore, we propose a novel style injection technique that enables controllable style transfer for the injected text. Through comprehensive experiments, we demonstrate the state-of-the-art performance of our method.