5 papers
RoG-DAgger: Rollout-Guided Post-Training for End-to-End Driving
Liangyu Zhong, Joachim Sicking, Fabian Hueger +1
Recent end-to-end driving systems demonstrate strong performance on closed-loop benchmarks, yet are still predominantly trained on fixed expert-collected data using open-loop imita…
Spatio-Temporal Attention for Consistent Video Semantic Segmentation in Automated Driving
Serin Varghese, Kevin Ross, Fabian Hueger +1
Deep neural networks, especially transformer-based architectures, have achieved remarkable success in semantic segmentation for environmental perception. However, existing models p…
Plants Don't Walk on the Street: Common-Sense Reasoning for Reliable Semantic Segmentation
Linara Adilova, Elena Schulz, Maram Akila +4
Data-driven sensor interpretation in autonomous driving can lead to highly implausible predictions as can most of the time be verified with common-sense knowledge. However, learnin…
Street-Map Based Validation of Semantic Segmentation in Autonomous Driving
Laura von Rueden, Tim Wirtz, Fabian Hueger +3
Artificial intelligence for autonomous driving must meet strict requirements on safety and robustness, which motivates the thorough validation of learned models. However, current v…
Towards Map-Based Validation of Semantic Segmentation Masks
Laura von Rueden, Tim Wirtz, Fabian Hueger +2
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…