VIS30K: A Collection of Figures and Tables from IEEE Visualization Conference Publications
Abstract
We present the VIS30K dataset, a collection of 29,689 images that represents 30 years of figures and tables from each track of the IEEE Visualization conference series (Vis, SciVis, InfoVis, VAST). VIS30K’s comprehensive coverage of the scientific literature in visualization not only reflects the progress of the field but also enables researchers to study the evolution of the state-of-the-art and to find relevant work based on graphical content. We describe the dataset and our semi-automatic collection process, which couples convolutional neural networks (CNN) with curation. Extracting figures and tables semi-automatically allows us to verify that no images are overlooked or extracted erroneously. To improve quality further, we engaged in a peer-search process for high-quality figures from early IEEE Visualization papers. With the resulting data, we also contribute VISImageNavigator (VIN, visimagenavigator.github.io), a web-based tool that facilitates searching and exploring VIS30K by author names, paper keywords, title and abstract, and years.
Domains
Computer science
Fichier principal
Chen_2021_VCF.pdf (21.42 Mo)
Télécharger le fichier
thumbnail.png (398.61 Ko)
Télécharger le fichier
Origin : Files produced by the author(s)
Licence : Copyright
Licence : Copyright
Format : Figure, Image
Licence : CC BY - Attribution
Licence : CC BY - Attribution