Marius Schubert

17 papers A 2B 1Journal 9Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	LMD: Light-Weight Prediction Quality Estimation for Object Detection in Lidar Point Clouds. Int. J. Comput. Vis. Tobias Riedlinger, Marius Schubert, Sarina Penquitt, Jan-Marcel Kezmann, Pascal Colling, Karsten Kahl, Lutz Roese-Koerner, Michael Arnold, Urs Zimmermann, Matthias Rottmann
2024	—	`conf`	Deep Active Learning with Noisy Oracle in Object Detection. VISIGRAPP (2): VISAPP Marius Schubert, Tobias Riedlinger, Karsten Kahl, Matthias Rottmann
2024	A	`conf`	Identifying Label Errors in Object Detection Datasets by Loss Inspection. WACV Marius Schubert, Tobias Riedlinger, Karsten Kahl, Daniel Kröll, Sebastian Schoenen, Sinisa Segvic, Matthias Rottmann
2024	—	`conf`	Towards Rapid Prototyping and Comparability in Active Learning for Deep Object Detection. VISIGRAPP (2): VISAPP Tobias Riedlinger, Marius Schubert, Karsten Kahl, Hanno Gottschalk, Matthias Rottmann
2023	J	`jnl`	Deep Active Learning with Noisy Oracle in Object Detection. CoRR Marius Schubert, Tobias Riedlinger, Karsten Kahl, Matthias Rottmann
2023	A	`conf`	Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors. WACV Tobias Riedlinger, Matthias Rottmann, Marius Schubert, Hanno Gottschalk
2023	J	`jnl`	Identifying Label Errors in Object Detection Datasets by Loss Inspection. CoRR Marius Schubert, Tobias Riedlinger, Karsten Kahl, Daniel Kröll, Sebastian Schoenen, Sinisa Segvic, Matthias Rottmann
2023	—	`conf`	LMD: Light-Weight Prediction Quality Estimation for Object Detection in Lidar Point Clouds. DAGM Tobias Riedlinger, Marius Schubert, Sarina Penquitt, Jan-Marcel Kezmann, Pascal Colling, Karsten Kahl, Lutz Roese-Koerner, Michael Arnold, Urs Zimmermann, Matthias Rottmann
2023	J	`jnl`	LMD: Light-weight Prediction Quality Estimation for Object Detection in Lidar Point Clouds. CoRR Tobias Riedlinger, Marius Schubert, Sarina Penquitt, Jan-Marcel Kezmann, Pascal Colling, Karsten Kahl, Lutz Roese-Koerner, Michael Arnold, Urs Zimmermann, Matthias Rottmann
2023	—	`—`	Uncertainty Quantification Methods and their Applications in Object Detection. Marius Schubert
2022	J	`jnl`	Towards Rapid Prototyping and Comparability in Active Learning for Deep Object Detection. CoRR Tobias Riedlinger, Marius Schubert, Karsten Kahl, Hanno Gottschalk, Matthias Rottmann
2022	J	`jnl`	Uncertainty Quantification and Resource-Demanding Computer Vision Applications of Deep Learning. CoRR Julian Burghoff, Robin Chan, Hanno Gottschalk, Annika Mütze, Tobias Riedlinger, Matthias Rottmann, Marius Schubert
2021	J	`jnl`	Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors. CoRR Tobias Riedlinger, Matthias Rottmann, Marius Schubert, Hanno Gottschalk
2021	B	`conf`	MetaDetect: Uncertainty Quantification and Prediction Quality Estimates for Object Detection. IJCNN Marius Schubert, Karsten Kahl, Matthias Rottmann
2020	J	`jnl`	MetaDetect: Uncertainty Quantification and Prediction Quality Estimates for Object Detection. CoRR Marius Schubert, Karsten Kahl, Matthias Rottmann
2019	—	`conf`	Uncertainty Measures and Prediction Quality Rating for the Semantic Segmentation of Nested Multi Resolution Street Scene Images. CVPR Workshops Matthias Rottmann, Marius Schubert
2019	J	`jnl`	Uncertainty Measures and Prediction Quality Rating for the Semantic Segmentation of Nested Multi Resolution Street Scene Images. CoRR Matthias Rottmann, Marius Schubert