论文标题
神经风格差异转移及其在字体生成中的应用
Neural Style Difference Transfer and Its Application to Font Generation
论文作者
论文摘要
设计字体需要大量时间和精力。它需要专业技能，例如草图，矢量化和图像编辑。此外，每个字母都必须单独设计。在本文中，我们将介绍一种自动创建字体的方法。在我们提出的方法中，找到了两种不同字体之间的字体样式差异，并使用神经样式传输转移到另一种字体中。神经样式转移是一种使用另一个图像样式的图像内容进行样式化的方法。我们提出了一种新颖的神经风格差异和神经风格转移的内容差异损失。通过这些损失，可以通过从字体添加或删除字体样式来生成新字体。我们提供了通过输入字体的各种组合，讨论了所提出方法的局限性和未来开发的实验结果。
Designing fonts requires a great deal of time and effort. It requires professional skills, such as sketching, vectorizing, and image editing. Additionally, each letter has to be designed individually. In this paper, we will introduce a method to create fonts automatically. In our proposed method, the difference of font styles between two different fonts is found and transferred to another font using neural style transfer. Neural style transfer is a method of stylizing the contents of an image with the styles of another image. We proposed a novel neural style difference and content difference loss for the neural style transfer. With these losses, new fonts can be generated by adding or removing font styles from a font. We provided experimental results with various combinations of input fonts and discussed limitations and future development for the proposed method.
