Marius Schubert

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 15

Top Topics

Object Detection

Top Venues

VISIGRAPP (2): VISAPP

Publications

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