2 citations · 4 across the 3 of their papers we have counts for
3 papers
Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness
Steven Landgraf, Markus Hillemann, Markus Ulrich
Semantic segmentation is critical for scene understanding but demands costly pixel-wise annotations, attracting increasing attention to semi-supervised approaches to leverage abund…
Efficient Multi-task Uncertainties for Joint Semantic Segmentation and Monocular Depth Estimation
Steven Landgraf, Markus Hillemann, Theodor Kapler +1
Quantifying the predictive uncertainty emerged as a possible solution to common challenges like overconfidence or lack of explainability and robustness of deep neural networks, alb…
U-CE: Uncertainty-aware Cross-Entropy for Semantic Segmentation
Steven Landgraf, Markus Hillemann, Kira Wursthorn +1
Deep neural networks have shown exceptional performance in various tasks, but their lack of robustness, reliability, and tendency to be overconfident pose challenges for their depl…