The quality of semantic image segmentation models can be affected by external factors such as weather or daytime. Those factors can lead to safety-critical mistakes. In this work, …
We propose a pixel-accurate failure prediction approach for semantic video segmentation. The proposed scheme improves previously proposed failure prediction methods which so far …
In autonomous driving, complex traffic scenarios can cause situations that require human supervision to resolve safely. Instead of only reacting to such events, it is desirable to …
With increasing progress in autonomous driving, the human does not have to be in control of the vehicle for the entire drive. A human driver obtains the control of the vehicle in …
Accurate visual scene perception plays an important role in fields such as medical imaging or autonomous driving. Recent advances in computer vision allow for accurate image …
Teleoperated driving (TOD) is a possible solution to cope with failures of autonomous vehicles. In TOD, the human operator perceives the traffic situation via video streams of …
Teledriving is a possible fallback mode to cope with failures of fully autonomous vehicles. One important requirement for teleoperated vehicles is a reliable low delay data …
Failures in autonomous driving caused by complex traffic situations or model inaccuracies remain inevitable in the near future. While much research is focused on how to prevent …
Visual environment perception is one of the key elements for autonomous and manual driving. Modern fully automated vehicles are equipped with a range of different sensors and …
Semantic segmentation of images enables pixel-wise scene understanding which in turn is a critical component for tasks such as autonomous driving. While recent implementations of …