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Learning Implicit Glyph Shape Representation.

作者信息

Liu Ying-Tian, Guo Yuan-Chen, Li Yi-Xiao, Wang Chen, Zhang Song-Hai

出版信息

IEEE Trans Vis Comput Graph. 2023 Oct;29(10):4172-4182. doi: 10.1109/TVCG.2022.3183400. Epub 2023 Sep 1.

DOI:10.1109/TVCG.2022.3183400
PMID:35709112
Abstract

Automatic generation of fonts can greatly facilitate the font design process, and provide prototypes where designers can draw inspiration from. Existing generation methods are mainly built upon rasterized glyph images to utilize the successful convolutional architecture, but ignore the vector nature of glyph shapes. We present an implicit representation, modeling each glyph as shape primitives enclosed by several quadratic curves. This structured implicit representation is shown to be better suited for glyph modeling, and enables rendering glyph images at arbitrary high resolutions. Our representation gives high-quality glyph reconstruction and interpolation results, and performs well on the challenging one-shot font style transfer task comparing to other alternatives both qualitatively and quantitatively.

摘要

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