29 citations · 86 across the 22 of their papers we have counts for
5 papers · 1 filter
A Probabilistic Perspective on Wasserstein-Based Evidential Uncertainty for Out-of-Distribution Segmentation
Arnold Brosch, Abdelrahman Eldesokey, Michael Felsberg +1
Semantic segmentation networks operate on a fixed set of classes and therefore fail when out-of-distribution (OOD) objects appear during deployment, a critical limitation for safet…
Combining Foundation Model Confidence and Monocular Depth for Training-Free Out-of-Distribution Segmentation
Serin Varghese, Fabian Hüger, Kira Maag
Autonomous vehicles operating in open-world scenarios are inevitably confronted with previously unknown objects, such as exotic animals or loose cargo. The reliable detection and s…
Extended Field of View Analysis for VideoGAN-based Trajectory Generation
Annajoyce Mariani, Kira Maag, Hanno Gottschalk
Realistic and diverse trajectory generation is central to enabling higher levels of vehicle automation. While rule-based and classical learning-based methods may struggle to captur…
Texture-Shape Bias Balancing for Robust Synthetic-to-Real Semantic Segmentation in Automotive NIR Imagery
Felix Stillger, Ben Hamscher, Lukas Hahn +3
Semantic segmentation is a fundamental component of visual perception in modern automotive systems, enabling pixel-level scene understanding. Near-Infrared imaging (NIR) offers sta…
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…