no code implementations • ECCV 2020 • Christoph Kamann, Burkhard Güssefeld, Robin Hutmacher, Jan Hendrik Metzen, Carsten Rother
With respect to our 16 different types of image corruptions and 5 different network backbones, we are in 74% better than training with clean data.
no code implementations • CVPR 2020 • Christoph Kamann, Carsten Rother
When designing a semantic segmentation module for a practical application, such as autonomous driving, it is crucial to understand the robustness of the module with respect to a wide range of image corruptions.