Impressions2Font：通过字体映像生成字体
Impressions2Font: Generating Fonts by Specifying Impressions
摘要：
不同的字体给我们不同的印象，这些印象通常用文字来表示。本文提出了Impressions2Font（Imp2Font），生成具有特定印象的字体图像。Imp2Font是条件生成对抗网络（GANs）的扩展版本。更准确地说，Imp2Font接受任意数量的印象词作为生成字体图像的条件。这些印象词被基于词嵌入技术构建的印象嵌入模块转换成软约束向量。定性和定量的评价证明，Imp2Font生成的字体图像质量比比较方法，通过提供多个印象词，甚至未学习的单词。
英文摘要：
Various fonts give us various impressions, which are often represented by words. This paper proposes Impressions2Font (Imp2Font) that generates font images with specific impressions. Imp2Font is an extended version of conditional generative adversarial networks (GANs). More precisely, Imp2Font accepts an arbitrary number of impression words as the condition to generate the font images. These impression words are converted into a soft-constraint vector by an impression embedding module built on a word embedding technique. Qualitative and quantitative evaluations prove that Imp2Font generates font images with higher quality than comparative methods by providing multiple impression words or even unlearned words.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
