Marius Schubert

According to our database, Marius Schubert authored at least 8 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Identifying Label Errors in Object Detection Datasets by Loss Inspection.

Marius Schubert, Tobias Riedlinger, Karsten Kahl, Daniel Kröll, Sebastian Schoenen, Sinisa Segvic, Matthias Rottmann

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Deep Active Learning with Noisy Oracle in Object Detection.

Marius Schubert, Tobias Riedlinger, Karsten Kahl, Matthias Rottmann

Proceedings of the 19th International Joint Conference on Computer Vision, 2024

Towards Rapid Prototyping and Comparability in Active Learning for Deep Object Detection.

Tobias Riedlinger, Marius Schubert, Karsten Kahl, Hanno Gottschalk, Matthias Rottmann

Proceedings of the 19th International Joint Conference on Computer Vision, 2024

2023

Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors.

Tobias Riedlinger, Matthias Rottmann, Marius Schubert, Hanno Gottschalk

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

LMD: Light-Weight Prediction Quality Estimation for Object Detection in Lidar Point Clouds.

Tobias Riedlinger, Marius Schubert, Sarina Penquitt, Jan-Marcel Kezmann, Pascal Colling, Karsten Kahl, Lutz Roese-Koerner, Michael Arnold, Urs Zimmermann, Matthias Rottmann

Proceedings of the Pattern Recognition - 45th DAGM German Conference, 2023

2022

Uncertainty Quantification and Resource-Demanding Computer Vision Applications of Deep Learning.

Julian Burghoff, Robin Chan, Hanno Gottschalk, Annika Mütze, Tobias Riedlinger, Matthias Rottmann, Marius Schubert

CoRR, 2022

2021

MetaDetect: Uncertainty Quantification and Prediction Quality Estimates for Object Detection.

Marius Schubert, Karsten Kahl, Matthias Rottmann

Proceedings of the International Joint Conference on Neural Networks, 2021

2019

Uncertainty Measures and Prediction Quality Rating for the Semantic Segmentation of Nested Multi Resolution Street Scene Images.

Matthias Rottmann, Marius Schubert

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019