Maria Lyssenko — accepted AI-conference papers

2024

A Safety-Adapted Loss for Pedestrian Detection in Autonomous Driving

Maria Lyssenko, Piyush Pimplikar, Maarten Bieshaar, Farzad Nozarian, Rudolph Triebel

ICRA 2024poster

In safety-critical domains like autonomous driving (AD), errors by the object detector may endanger pedestrians and other vulnerable road users (VRU). As raw evaluation metrics are not an adequate safety indicator, recent works leverage domain knowledge to identify safety-relevant VRU, and to back-a…

Cited by 1 Source ↗Scholar ↗

2022

Towards Safety-Aware Pedestrian Detection in Autonomous Systems

Maria Lyssenko, Christoph Gladisch, Christian Heinzemann, Matthias Woehrle, Rudolph Triebel

IROS 2022poster

In this paper, we present a framework to assess the quality of a pedestrian detector in an autonomous driving scenario. To do this, we exploit performance metrics from the domain of computer vision on one side and so-called threat metrics from the motion planning domain on the other side. Based on a…

Cited by 14 Source ↗Scholar ↗