首个统一评分与优化设计的智能工具，提升视觉吸引力。
Design-o-meter: Towards Evaluating and Refining Graphic Designs
- 基于数据驱动框架，统一评估与优化图形设计
- 相比主流方法显著提升评分准确率与优化效果
- 适合设计师、AI内容生产者快速迭代作品
图形设计是有效的视觉传播媒介，涵盖贺卡、企业传单等多种形式。近年来，机器学习技术已能生成此类设计，加速内容生产，因此自动化评估设计质量变得至关重要。为此，我们提出 Design-o-meter——一种数据驱动的方法，用于量化图形设计的质量，并可建议修改以提升视觉吸引力。据我们所知，Design-o-meter 是首个在统一框架内完成评分与优化的设计评估方法，克服了该任务固有的主观性与模糊性。我们对所提方法进行了全面的定量与定性分析，对比了适配该任务的基线模型（包括近期基于多模态大模型的方法），验证了其有效性。我们希望本工作能激发更多对这一重要且实际问题的关注。
原文摘要 · Abstract (English)
Graphic designs are an effective medium for visual communication. They range from greeting cards to corporate flyers and beyond. Off-late, machine learning techniques are able to generate such designs, which accelerates the rate of content production. An automated way of evaluating their quality becomes critical. Towards this end, we introduce Design-o-meter, a data-driven methodology to quantify the goodness of graphic designs. Further, our approach can suggest modifications to these designs to improve its visual appeal. To the best of our knowledge, Design-o-meter is the first approach that scores and refines designs in a unified framework despite the inherent subjectivity and ambiguity of the setting. Our exhaustive quantitative and qualitative analysis of our approach against baselines adapted for the task (including recent Multimodal LLM-based approaches) brings out the efficacy of our methodology. We hope our work will usher more interest in this important and pragmatic problem setting.
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