In the field of graphic design, automating the integration of design elements
into a cohesive multi-layered artwork not only boosts productivity but also
paves the way for the democratization of graphic design. One existing practice
is Graphic Layout Generation (GLG), which aims to layout sequential design
elements. It has been constrained by the necessity for a predefined correct
sequence of layers, thus limiting creative potential and increasing user
workload. In this paper, we present Hierarchical Layout Generation (HLG) as a
more flexible and pragmatic setup, which creates graphic composition from
unordered sets of design elements. To tackle the HLG task, we introduce
Graphist, the first layout generation model based on large multimodal models.
Graphist efficiently reframes the HLG as a sequence generation problem,
utilizing RGB-A images as input, outputs a JSON draft protocol, indicating the
coordinates, size, and order of each element. We develop new evaluation metrics
for HLG. Graphist outperforms prior arts and establishes a strong baseline for
this field. Project homepage: this https URL

在图形设计领域，自动化地将设计元素整合为一个连贯的多层艺术作品不仅提高了工作效率，还为图形设计的大众化铺平了道路。本文介绍了一种称为 Hierarchical Layout Generation (HLG) 的更灵活和实用的设置，它从无序的设计元素集合中创建图形构图。通过基于大型多模态模型的图形生成模型 Graphist，我们有效地将 HLG 作为一个序列生成问题来解决，并利用 RGB-A 图像作为输入，输出一个 JSON 草稿协议，指示每个元素的坐标、大小和顺序。我们开发了新的 HLG 评估指标，Graphist 在性能上超过了以往的技术，为该领域奠定了坚实的基础。项目主页：[此处为项目主页的链接]