论文标题
矢量图形文档的颜色建议基于多板表示
Color Recommendation for Vector Graphic Documents based on Multi-Palette Representation
论文作者
论文摘要
向量图形文档呈现多个视觉元素，例如图像，形状和文本。对于业余爱好者和专业设计师来说，为多个视觉元素选择合适的颜色是一项艰巨但至关重要的任务。我们没有为所有元素创建单个调色板，而是从图形文档中的每个视觉元素中提取多个调色板，然后将它们组合成颜色序列。我们为颜色序列完成提出了一个蒙版的颜色模型，并根据多板中的颜色上下文推荐了指定的颜色，概率很高。我们在矢量图形文档的大规模数据集上训练模型并构建颜色推荐系统。提出的颜色建议方法在访谈研究中，对颜色预测的定量和定性评估都优于其他最先进的方法，而我们的颜色推荐系统则获得了专业设计师的积极反馈。
Vector graphic documents present multiple visual elements, such as images, shapes, and texts. Choosing appropriate colors for multiple visual elements is a difficult but crucial task for both amateurs and professional designers. Instead of creating a single color palette for all elements, we extract multiple color palettes from each visual element in a graphic document, and then combine them into a color sequence. We propose a masked color model for color sequence completion and recommend the specified colors based on color context in multi-palette with high probability. We train the model and build a color recommendation system on a large-scale dataset of vector graphic documents. The proposed color recommendation method outperformed other state-of-the-art methods by both quantitative and qualitative evaluations on color prediction and our color recommendation system received positive feedback from professional designers in an interview study.
