Ad-datasets: A Meta-collection of Data Sets for Autonomous Driving

Daniel Bogdoll, Daniel Bogdoll, Felix Schreyer, J. Zöllner, J. Zöllner

2022

Abstract

Autonomous driving is among the largest domains in which deep learning has been fundamental for progress within the last years. The rise of datasets went hand in hand with this development. All the more striking is the fact that researchers do not have a tool available that provides a quick, comprehensive and up-to-date overview of data sets and their features in the domain of autonomous driving. In this paper, we present ad-datasets, an online tool that provides such an overview for more than 150 data sets. The tool enables users to sort and filter the data sets according to currently 16 different categories. ad-datasets is an open-source project with community contributions. It is in constant development, ensuring that the content stays up-to-date.

Paper Citation

in Harvard Style

Bogdoll D., Schreyer F. and Zöllner J. (2022). Ad-datasets: A Meta-collection of Data Sets for Autonomous Driving. In Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-573-9, pages 46-56. DOI: 10.5220/0011001900003191

in Bibtex Style

@conference{vehits22,
author={Daniel Bogdoll and Felix Schreyer and J. Zöllner},
title={Ad-datasets: A Meta-collection of Data Sets for Autonomous Driving},
booktitle={Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2022},
pages={46-56},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011001900003191},
isbn={978-989-758-573-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - Ad-datasets: A Meta-collection of Data Sets for Autonomous Driving
SN - 978-989-758-573-9
AU - Bogdoll D.
AU - Schreyer F.
AU - Zöllner J.
PY - 2022
SP - 46
EP - 56
DO - 10.5220/0011001900003191