Modeling layout is an important first step for graphic design. Recently, methods for generating graphic layouts have progressed, particularly with Generative Adversarial Networks (GANs). However, the problem of specifying the locations and sizes of design elements usually involves constraints with respect to element attributes, such as area, aspect ratio and reading-order. Automating attribute conditional graphic layouts remains a complex and unsolved problem. In this paper, we introduce Attribute-conditioned Layout GAN to incorporate the attributes of design elements for graphic layout generation by forcing both the generator and the discriminator to meet attribute conditions. Due to the complexity of graphic designs, we further propose an element dropout method to make the discriminator look at partial lists of elements and learn their local patterns. In addition, we introduce various loss designs following different design principles for layout optimization. We demonstrate that the proposed method can synthesize graphic layouts conditioned on different element attributes. It can also adjust well-designed layouts to new sizes while retaining elements' original reading-orders. The effectiveness of our method is validated through a user study.

中文翻译：

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用于自动图形设计的属性条件布局 GAN

建模布局是平面设计的重要第一步。最近，生成图形布局的方法取得了进展，尤其是生成对抗网络 (GAN)。然而，指定设计元素的位置和大小的问题通常涉及元素属性的约束，例如面积、纵横比和阅读顺序。自动化属性条件图形布局仍然是一个复杂且未解决的问题。在本文中，我们引入了属性条件布局 GAN，通过强制生成器和鉴别器都满足属性条件来合并图形布局生成的设计元素的属性。由于图形设计的复杂性，我们进一步提出了一种元素丢弃方法，使鉴别器查看元素的部分列表并学习它们的局部模式。此外，我们根据布局优化的不同设计原则介绍了各种损耗设计。我们证明了所提出的方法可以合成以不同元素属性为条件的图形布局。它还可以将精心设计的布局调整为新的尺寸，同时保留元素的原始阅读顺序。通过用户研究验证了我们方法的有效性。原始阅读顺序。通过用户研究验证了我们方法的有效性。原始阅读顺序。通过用户研究验证了我们方法的有效性。