Automated driving systems (ADSs) aim to improve the safety, efficiency and comfort of future
vehicles. To achieve this, ADSs use sensors to collect raw data from their environment. This …

Semantic segmentation is an important task that helps autonomous vehicles understand
their surroundings and navigate safely. However, during deployment, even the most mature …

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 case of an …

We present an introspective failure prediction approach for autonomous vehicles. In
autonomous driving, complex or unknown scenarios can cause a disengagement of the self …

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 predict …

We propose a pixel-accurate failure prediction approach for semantic video segmentation.
The proposed scheme improves previously proposed failure prediction methods which so …

Road segmentation is an essential component of navigation systems. Although recent
advancements in road segmentation, the occurrence of failure segmentations remains …

The knee joint, due to its complex, confined, and dynamic nature, poses several challenges
in visualizing anatomical details for diagnostic and minimally invasive surgical procedures …

We propose the concept of error-reversing autoencoders (ERA) for correcting pixel-wise
errors made by an arbitrary semantic segmentation model. For this, we reframe the …

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 …