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|a 10.1109/TVCG.2022.3155440
|2 doi
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|a eng
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1 |
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|a Deng, Dazhen
|e verfasserin
|4 aut
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| 245 |
1 |
0 |
|a VisImages
|b A Fine-Grained Expert-Annotated Visualization Dataset
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| 264 |
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|c 2023
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|a Text
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Completed 28.05.2023
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|a Date Revised 28.05.2023
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a 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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| 650 |
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4 |
|a Journal Article
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| 700 |
1 |
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|a Wu, Yihong
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Shu, Xinhuan
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Wu, Jiang
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Fu, Siwei
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Cui, Weiwei
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Wu, Yingcai
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on visualization and computer graphics
|d 1996
|g 29(2023), 7 vom: 07. Juli, Seite 3298-3311
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|g volume:29
|g year:2023
|g number:7
|g day:07
|g month:07
|g pages:3298-3311
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|u http://dx.doi.org/10.1109/TVCG.2022.3155440
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