Layout design is an important task in various design fields, including user interfaces, document, and graphic design. As this task requires tedious manual effort by designers, prior works have attempted to automate this process using generative models, but commonly fell short of providing intuitive user controls and achieving design objectives. In this paper, we build a conditional latent diffusion model, PLay, that generates parametrically conditioned layouts in vector graphic space from user-specified guidelines, which are commonly used by designers for representing their design intents in current practices. Our method outperforms prior works across three datasets on metrics including FID and FD-VG, and in user test. Moreover, it brings a novel and interactive experience to professional layout design processes.
翻译:设计布局设计是各种设计领域的重要任务,包括用户界面、文档和图形设计。由于这项任务需要设计师的烦琐手工努力,先前的工程曾试图使用基因模型使这一过程自动化,但通常没有提供直观的用户控制,也没有达到设计目标。在本文中,我们建立了一个有条件的潜在传播模型,即Play,该模型从用户指定的指南中生成矢量图形空间的参数性条件布局,设计师通常使用该模型来在目前的做法中代表设计意图。我们的方法比以往的三种数据集(包括FID和FD-VG)以及用户测试中的工作要好。此外,它给专业的布局设计过程带来了新的互动经验。