iPoster: Content-Aware Layout Generation for Interactive Poster Design via Graph-Enhanced Diffusion Models
This addresses the need for more controllable and responsive design tools for poster creators, though it appears incremental as it builds on existing diffusion models.
The authors tackled the problem of interactive poster layout generation by developing iPoster, a framework that allows users to specify constraints like element categories and positions, and it generates refined layouts with state-of-the-art quality.
We present iPoster, an interactive layout generation framework that empowers users to guide content-aware poster layout design by specifying flexible constraints. iPoster enables users to specify partial intentions within the intention module, such as element categories, sizes, positions, or coarse initial drafts. Then, the generation module instantly generates refined, context-sensitive layouts that faithfully respect these constraints. iPoster employs a unified graph-enhanced diffusion architecture that supports various design tasks under user-specified constraints. These constraints are enforced through masking strategies that precisely preserve user input at every denoising step. A cross content-aware attention module aligns generated elements with salient regions of the canvas, ensuring visual coherence. Extensive experiments show that iPoster not only achieves state-of-the-art layout quality, but offers a responsive and controllable framework for poster layout design with constraints.