Paper
27 March 2024 Research on vector fonts generation based on hierarchical decoupling model
Author Affiliations +
Proceedings Volume 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023); 131052X (2024) https://doi.org/10.1117/12.3026326
Event: 3rd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 2023, Qingdao, China
Abstract
As an essential part of media content creativity, vector fonts are widely used in graphic design and embedded applications for their convenient editing transformations and high-quality display and output effects. However, designing high-quality vector Chinese fonts requires the designer's expertise, experience, creative inspiration, time, and effort. Therefore, it is of great practical significance to study efficient vector Chinese font generation methods to improve production efficiency and liberate manpower. For this reason, it is time-consuming and labor-intensive to manually create vector Chinese fonts with a uniform style. This paper proposes a hierarchical decoupling model (T-HD) based on Transformer. The goal of generating complex vector Chinese fonts from a single font style reference and content reference is realized. This paper proposes a hierarchical decoupling model (T-HD) based on Transformer.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yalin Miao, Yaoxin Nie, Wangqiang Liu, Wenxin Gao, Wanting Bai, Jiuling Wang, and Yixin Yang "Research on vector fonts generation based on hierarchical decoupling model", Proc. SPIE 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 131052X (27 March 2024); https://doi.org/10.1117/12.3026326
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KEYWORDS
Data modeling

Deep learning

Machine learning

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