Diffusion models have gained increasing attention for their impressive generation abilities
but currently struggle with rendering accurate and coherent text. To address this issue, we …

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 …

The diffusion model has been proven a powerful generative model in recent years, yet it
remains a challenge in generating visual text. Although existing work has endeavored to …

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 …

Document intelligence automates the extraction of information from documents and supports
many business applications. Recent self-supervised learning methods on large-scale …

Generative models able to synthesize layouts of different kinds (eg documents, user
interfaces or furniture arrangements) are a useful tool to aid design processes and as a first …

We address the problem of scene layout generation for diverse domains such as images,
mobile applications, documents, and 3D objects. Most complex scenes, natural or human …

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 …

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 …