论文标题
Visimages：细粒度的专家宣布的可视化数据集
VisImages: A Fine-Grained Expert-Annotated Visualization Dataset
论文作者
论文摘要
可视化出版物中的图像包含丰富的信息，例如新颖的可视化设计和内隐设计模式。这些图像的系统集合可以在许多方面为社区做出贡献，例如文献分析和可视化的自动化任务。在本文中，我们构建并使公共一个数据集，Vibimages，该数据集收集了12,267张图像，并带有来自IEEE Infovis和Gast的1,397篇论文的标题。该数据集建立在全面的可视化分类法上，包括35,096个可视化及其边界框。我们在三种用例中演示了构现象的有用性：1）调查具有Visimages Explorer的可视化使用，2）培训和基准分类模型进行可视化分析，以及3）自动可视化的可视化分析。
Images in visualization publications contain rich information, e.g., novel visualization designs and implicit design patterns of visualizations. A systematic collection of these images can contribute to the community in many aspects, such as literature analysis and automated tasks for visualization. In this paper, we build and make public a dataset, VisImages, which collects 12,267 images with captions from 1,397 papers in IEEE InfoVis and VAST. Built upon a comprehensive visualization taxonomy, the dataset includes 35,096 visualizations and their bounding boxes in the images.We demonstrate the usefulness of VisImages through three use cases: 1) investigating the use of visualizations in the publications with VisImages Explorer, 2) training and benchmarking models for visualization classification, and 3) localizing visualizations in the visual analytics systems automatically.
