Towards Map-Based Validation of Semantic Segmentation Masks

Author: L. von Rueden, T. Wirtz, F. Hueger, J. D. Schneider, C. Bauckhage
Journal: AIAD Workshop at ICML
Year: 2020

Citation information

L. von Rueden, T. Wirtz, F. Hueger, J. D. Schneider, C. Bauckhage,
AIAD Workshop at ICML,
2020,
https://doi.org/10.48550/arXiv.2011.08008

Artificial intelligence for autonomous driving must meet strict requirements on safety and robustness. We propose to validate machine learning models for self-driving vehicles not only with given ground truth labels, but also with additional a-priori knowledge. In particular, we suggest to validate the drivable area in semantic segmentation masks using given street map data. We present first results, which indicate that prediction errors can be uncovered by map-based validation.