VIS30K

Autor(en)

Jian Chen, Meng Ling, Rui Li, Petra Isenberg, Tobias Isenberg, Michael Sedlmair, Torsten Möller, Robert S. Laramee, Han-Wei Shen, Katharina Wünsche, Qiru Wang

Abstrakt

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.

Organisation(en)

Forschungsgruppe Visualization and Data Analysis, Institut für Innovation und Digitalisierung im Recht

Externe Organisation(en)

Ohio State University, Université Paris Saclay, Universität Stuttgart, University of Nottingham

Journal

IEEE Transactions on Visualization and Computer Graphics

Band

27

Seiten

3826-3833

Anzahl der Seiten

8

DOI

https://doi.org/10.1109/TVCG.2021.3054916

Publikationsdatum

12-2020

Peer-reviewed

Ja

ÖFOS 2012

102037 Visualisierung, 102003 Bildverarbeitung, 102008 Computergraphik

Schlagwörter

ASJC Scopus Sachgebiete

Software, Signal Processing, Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design

Link zum Portal

https://ucrisportal.univie.ac.at/de/publications/vis30k(c2eb8024-3dc6-4cde-9e90-ed694caa9bfd).html