TextPainter: Multimodal Text Image Generation with Visual-harmony and Text-comprehension for Poster Design

• URL: http://arxiv.org/abs/2308.04733v3
• Date: Sun, 13 Aug 2023 03:11:55 GMT
• Title: TextPainter: Multimodal Text Image Generation with Visual-harmony and Text-comprehension for Poster Design
• Authors: Yifan Gao, Jinpeng Lin, Min Zhou, Chuanbin Liu, Hongtao Xie, Tiezheng Ge, Yuning Jiang
• Abstract summary: This study introduces TextPainter, a novel multimodal approach to generate text images. TextPainter takes the global-local background image as a hint of style and guides the text image generation with visual harmony. We construct the PosterT80K dataset, consisting of about 80K posters annotated with sentence-level bounding boxes and text contents.
• Score: 50.8682912032406
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Text design is one of the most critical procedures in poster design, as it relies heavily on the creativity and expertise of humans to design text images considering the visual harmony and text-semantic. This study introduces TextPainter, a novel multimodal approach that leverages contextual visual information and corresponding text semantics to generate text images. Specifically, TextPainter takes the global-local background image as a hint of style and guides the text image generation with visual harmony. Furthermore, we leverage the language model and introduce a text comprehension module to achieve both sentence-level and word-level style variations. Besides, we construct the PosterT80K dataset, consisting of about 80K posters annotated with sentence-level bounding boxes and text contents. We hope this dataset will pave the way for further research on multimodal text image generation. Extensive quantitative and qualitative experiments demonstrate that TextPainter can generate visually-and-semantically-harmonious text images for posters.

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