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Marius Schubert
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2020 – today
- 2024
- [c7]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: 366-374 - [c6]Marius Schubert, Tobias Riedlinger, Karsten Kahl, Matthias Rottmann:
Deep Active Learning with Noisy Oracle in Object Detection. VISIGRAPP (2): VISAPP 2024: 375-384 - [c5]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: 4570-4579 - 2023
- [b1]Marius Schubert:
Uncertainty Quantification Methods and their Applications in Object Detection. University of Wuppertal, Germany, 2023 - [c4]Tobias Riedlinger
, Marius Schubert
LMD: Light-Weight Prediction Quality Estimation for Object Detection in Lidar Point Clouds. DAGM 2023: 85-99 - [c3]Tobias Riedlinger, Matthias Rottmann, Marius Schubert, Hanno Gottschalk:
Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors. WACV 2023: 3910-3920 - [i8]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 abs/2303.06999 (2023) - [i7]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 abs/2306.07835 (2023) - [i6]Marius Schubert, Tobias Riedlinger, Karsten Kahl, Matthias Rottmann:
Deep Active Learning with Noisy Oracle in Object Detection. CoRR abs/2310.00372 (2023) - 2022
- [i5]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 abs/2205.14917 (2022) - [i4]Tobias Riedlinger, Marius Schubert, Karsten Kahl, Hanno Gottschalk, Matthias Rottmann:
Towards Rapid Prototyping and Comparability in Active Learning for Deep Object Detection. CoRR abs/2212.10836 (2022) - 2021
- [c2]Marius Schubert, Karsten Kahl, Matthias Rottmann:
MetaDetect: Uncertainty Quantification and Prediction Quality Estimates for Object Detection. IJCNN 2021: 1-10 - [i3]Tobias Riedlinger, Matthias Rottmann, Marius Schubert, Hanno Gottschalk:
Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors. CoRR abs/2107.04517 (2021) - 2020
- [i2]Marius Schubert, Karsten Kahl, Matthias Rottmann:
MetaDetect: Uncertainty Quantification and Prediction Quality Estimates for Object Detection. CoRR abs/2010.01695 (2020)
2010 – 2019
- 2019
- [c1]Matthias Rottmann, Marius Schubert:
Uncertainty Measures and Prediction Quality Rating for the Semantic Segmentation of Nested Multi Resolution Street Scene Images. CVPR Workshops 2019: 1361-1369 - [i1]Matthias Rottmann, Marius Schubert:
Uncertainty Measures and Prediction Quality Rating for the Semantic Segmentation of Nested Multi Resolution Street Scene Images. CoRR abs/1904.04516 (2019)
Coauthor Index
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