49 citations · 58 across the 3 of their papers we have counts for
5 papers
Foundation Models for Amodal Video Instance Segmentation in Automated Driving
Jasmin Breitenstein, Franz Jünger, Andreas Bär +1
In this work, we study amodal video instance segmentation for automated driving. Previous works perform amodal video instance segmentation relying on methods trained on entirely la…
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety
Sebastian Houben, Stephanie Abrecht, Maram Akila +38
The use of deep neural networks (DNNs) in safety-critical applications like mobile health and autonomous driving is challenging due to numerous model-inherent shortcomings. These s…
Improving Online Performance Prediction for Semantic Segmentation
Marvin Klingner, Andreas Bär, Marcel Mross +1
In this work we address the task of observing the performance of a semantic segmentation deep neural network (DNN) during online operation, i.e., during inference, which is of high…
Towards Corner Case Detection for Autonomous Driving
Jan-Aike Bolte, Andreas Bär, Daniel Lipinski +1
The progress in autonomous driving is also due to the increased availability of vast amounts of training data for the underlying machine learning approaches. Machine learning syste…
GAN- vs. JPEG2000 Image Compression for Distributed Automotive Perception: Higher Peak SNR Does Not Mean Better Semantic Segmentation
Jonas Löhdefink, Andreas Bär, Nico M. Schmidt +3
The high amount of sensors required for autonomous driving poses enormous challenges on the capacity of automotive bus systems. There is a need to understand tradeoffs between bitr…