VisImages : A Fine-Grained Expert-Annotated Visualization Dataset
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....
| Veröffentlicht in: | IEEE transactions on visualization and computer graphics. - 1996. - 29(2023), 7 vom: 07. Juli, Seite 3298-3311 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2023
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on visualization and computer graphics |
| Schlagworte: | Journal Article |
| Zusammenfassung: | 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 |
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| Beschreibung: | Date Completed 28.05.2023 Date Revised 28.05.2023 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
| ISSN: | 1941-0506 |
| DOI: | 10.1109/TVCG.2022.3155440 |