Recent interest in design through the artificial intelligence (AI) lens is rapidly increasing.
Designers, as a special user group interacting with AI, have received more attention in the …

Controllable layout generation aims at synthesizing plausible arrangement of element
bounding boxes with optional constraints, such as type or position of a specific element. In …

Layout generation, as a crucial stage in Artificial Intelligence-Generated Content (AIGC) task
information presentation generation, is a fascinating and significant research topic …

In the text-to-image generation field, recent remarkable progress in Stable Diffusion makes it
possible to generate rich kinds of novel photorealistic images. However, current models still …

Creating graphic layouts is a fundamental step in graphic designs. In this work, we present a
novel generative model named LayoutDiffusion for automatic layout generation. As layout is …

Automatic layout generation that can synthesize high-quality layouts is an important tool for
graphic design in many applications. Though existing methods based on generative models …

Conditional graphic layout generation, which automatically maps user constraints to high-
quality layouts, has attracted widespread attention today. Although recent works have …

Layout generation aims to synthesize realistic graphic scenes consisting of elements with
different attributes including category, size, position, and between-element relation. It is a …

Creating visual layouts is a critical step in graphic design. Automatic generation of such
layouts is essential for scalable and diverse visual designs. To advance conditional layout …

Content-aware visual-textual presentation layout aims at arranging spatial space on the
given canvas for pre-defined elements, including text, logo, and underlay, which is a key to …