Graphic design is essential for visual communication with layouts being
fundamental to composing attractive designs. Layout generation differs from
pixel-level image synthesis and is unique in terms of the requirement of mutual
relations among the desired components. We propose a method for design layout
generation that can satisfy user-specified constraints. The proposed neural
design network (NDN) consists of three modules. The first module predicts a
graph with complete relations from a graph with user-specified relations. The
second module generates a layout from the predicted graph. Finally, the third
module fine-tunes the predicted layout. Quantitative and qualitative
experiments demonstrate that the generated layouts are visually similar to real
design layouts. We also construct real designs based on predicted layouts for a
better understanding of the visual quality. Finally, we demonstrate a practical
application on layout recommendation.

本文提出了一种利用神经设计网络 (NDN) 生成满足用户指定约束条件的设计布局的方法，被实验评估证明生成的设计布局与真实设计布局非常相似，并且在布局推荐方面具有实际应用价值。