Learning Implicit Glyph Shape Representation
Ying-Tian Liu, Yuan-Chen Guo, Yi-Xiao Li, Chen Wang, Song-Hai Zhang

TL;DR
This paper introduces a new implicit glyph shape representation using quadratic curves, enabling high-resolution image generation, effective font style transfer, and potential vector font conversion, advancing 2D shape modeling.
Contribution
The paper proposes a structured implicit glyph representation and a disentangled network for one-shot font style transfer, outperforming existing methods.
Findings
Effective for font reconstruction and interpolation
Achieves state-of-the-art results in style transfer
Potential for converting glyphs to vector fonts
Abstract
In this paper, we present a novel implicit glyph shape representation, which models glyphs as shape primitives enclosed by quadratic curves, and naturally enables generating glyph images at arbitrary high resolutions. Experiments on font reconstruction and interpolation tasks verified that this structured implicit representation is suitable for describing both structure and style features of glyphs. Furthermore, based on the proposed representation, we design a simple yet effective disentangled network for the challenging one-shot font style transfer problem, and achieve the best results comparing to state-of-the-art alternatives in both quantitative and qualitative comparisons. Benefit from this representation, our generated glyphs have the potential to be converted to vector fonts through post-processing, reducing the gap between rasterized images and vector graphics. We hope this…
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Taxonomy
TopicsGenerative Adversarial Networks and Image Synthesis · Advanced Vision and Imaging · Computer Graphics and Visualization Techniques
