Glyph-ByT5: A Customized Text Encoder for Accurate Visual Text Rendering
Abstract
Visual text rendering poses a fundamental challenge for contemporary text-to-image generation models, with the core problem lying in text encoder deficiencies. To achieve accurate text rendering, we identify two crucial requirements for text encoders: character awareness and alignment with glyphs.
Our solution involves crafting a series of customized text encoder, Glyph-ByT5, by fine-tuning the character-aware ByT5 encoder using a meticulously curated paired glyph-text dataset. We present an effective method for integrating Glyph-ByT5 with SDXL, resulting in the creation of the Glyph-SDXL model for design image generation. This significantly enhances text rendering accuracy, improving it from less than 20% to nearly 90% on our design image benchmark. Noteworthy is Glyph-SDXL's newfound ability for text paragraph rendering, achieving high spelling accuracy for tens to hundreds of characters with automated multi-line layouts.
Finally, through fine-tuning Glyph-SDXL with a small set of high-quality, photorealistic images featuring visual text, we showcase a substantial improvement in scene text rendering capabilities in open-domain real images. These compelling outcomes aim to encourage further exploration in designing customized text encoders for diverse and challenging tasks.
Method Overview
Glyph-ByT5 as a flexible region-wise visual text editor
Region-wise SDEdit pipeline
DALLE-3 image
Edited image
DALLE-3 image
Edited image
DALLE-3 image
Edited image
DALLE-3 image
Edited image
DALLE-3 image
Edited image
DALLE-3 image
Edited image
Typography layout planning with GPT-4
BibTeX
@misc{liu2024glyphbyt5,
title={Glyph-ByT5: A Customized Text Encoder for Accurate Visual Text Rendering},
author={Zeyu Liu and Weicong Liang and Zhanhao Liang and Chong Luo and Ji Li and Gao Huang and Yuhui Yuan},
year={2024},
eprint={2403.09622},
archivePrefix={arXiv},
primaryClass={cs.CV}
}