From Elements to Design: A Layered Approach for Automatic Graphic Design
  Composition
Authors: name: Jiawei Lin, name: Shizhao Sun, name: Danqing Huang, name: Ting Liu, name: Ji Li, name: Jiang Bian

In this work, we investigate automatic design composition from multimodal
graphic elements. Although recent studies have developed various generative
models for graphic design, they usually face the following limitations: they
only focus on certain subtasks and are far from achieving the design
composition task; they do not consider the hierarchical information of graphic
designs during the generation process. To tackle these issues, we introduce the
layered design principle into Large Multimodal Models (LMMs) and propose a
novel approach, called LaDeCo, to accomplish this challenging task.
Specifically, LaDeCo first performs layer planning for a given element set,
dividing the input elements into different semantic layers according to their
contents. Based on the planning results, it subsequently predicts element
attributes that control the design composition in a layer-wise manner, and
includes the rendered image of previously generated layers into the context.
With this insightful design, LaDeCo decomposes the difficult task into smaller
manageable steps, making the generation process smoother and clearer. The
experimental results demonstrate the effectiveness of LaDeCo in design
composition. Furthermore, we show that LaDeCo enables some interesting
applications in graphic design, such as resolution adjustment, element filling,
design variation, etc. In addition, it even outperforms the specialized models
in some design subtasks without any task-specific training.