用区域对比让海报更吸睛，无需训练即可生成美观设计。
ReContraster: Making Your Posters Stand Out with Regional Contrast
- 模拟设计师思维，用多智能体系统布局并评估海报
- 融合混合去噪策略，确保区域间过渡自然流畅
- 首个免训练的区域对比增强模型，适合会议海报设计
优秀的海报设计需快速吸引注意力并清晰传达信息。受‘对比效应’启发，我们提出ReContraster，首个无需训练的区域对比增强模型，使海报更具视觉冲击力。该模型通过仿照海报设计师的认知行为，引入组合式多智能体系统，识别元素、组织版式并评估生成的海报候选方案。为确保区域边界间的和谐过渡，ReContraster在扩散过程中集成混合去噪策略。我们还构建了一个新的基准数据集以支持全面评估。七个定量指标和四项用户研究验证了其优于现有方法的表现，生成的海报兼具视觉冲击力与审美吸引力。
原文摘要 · Abstract (English)
Effective poster design requires rapidly capturing attention and clearly conveying messages. Inspired by the ``contrast effects'' principle, we propose ReContraster, the first training-free model to leverage regional contrast to make posters stand out. By emulating the cognitive behaviors of a poster designer, ReContraster introduces the compositional multi-agent system to identify elements, organize layout, and evaluate generated poster candidates. To further ensure harmonious transitions across region boundaries, ReContraster integrates the hybrid denoising strategy during the diffusion process. We additionally contribute a new benchmark dataset for comprehensive evaluation. Seven quantitative metrics and four user studies confirm its superiority over relevant state-of-the-art methods, producing visually striking and aesthetically appealing posters.
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