10 citations · 12 across the 3 of their papers we have counts for
3 papers
Uncertainty Quantification with Deep Ensembles for 6D Object Pose Estimation
Kira Wursthorn, Markus Hillemann, Markus Ulrich
The estimation of 6D object poses is a fundamental task in many computer vision applications. Particularly, in high risk scenarios such as human-robot interaction, industrial inspe…
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…
DUDES: Deep Uncertainty Distillation using Ensembles for Semantic Segmentation
Steven Landgraf, Kira Wursthorn, Markus Hillemann +1
Deep neural networks lack interpretability and tend to be overconfident, which poses a serious problem in safety-critical applications like autonomous driving, medical imaging, or…