In:
Computer Science in Cars Symposium. ACM Computer Science in Cars Symposium (CSCS-2019) October 8-8 Kaiserslautern Germany ACM 2019.
Abstrakt
in this extended abstract, we provide an overview of SVIRO, arecently generated synthetic dataset for sceneries in the passengercompartment of ten different vehicles. We showed that SVIRO canbe used to analyze machine learning-based approaches for theirgeneralization capacities and reliability across several tasks whentrained on a limited number of variations (e.g. identical backgroundsand textures, few instances per class). This is in contrast to theintrinsically high variability of common benchmark datasets andas a result SVIRO allows investigations under novel circumstances.
@inproceedings{pub10758,
author = {Dias Da Cruz, Steve and Wasenmüller, Oliver and Beise, Hans-Peter and Stifter, Thomas and Stricker, Didier},
title = {An Overview of the SVIRO Dataset and Benchmark},
booktitle = {Computer Science in Cars Symposium. ACM Computer Science in Cars Symposium (CSCS-2019), October 8-8, Kaiserslautern, Germany},
year = {2019},
publisher = {ACM}
}
Deutsches Forschungszentrum für Künstliche Intelligenz German Research Center for Artificial Intelligence