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Marvin Klingner
Marvin Klingner
Verified email at tu-bs.de
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Self-supervised monocular depth estimation: Solving the dynamic object problem by semantic guidance
M Klingner, JA Termöhlen, J Mikolajczyk, T Fingscheidt
European Conference on Computer Vision, 582-600, 2020
1282020
Syndistnet: Self-supervised monocular fisheye camera distance estimation synergized with semantic segmentation for autonomous driving
VR Kumar, M Klingner, S Yogamani, S Milz, T Fingscheidt, P Mader
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021
412021
Improved noise and attack robustness for semantic segmentation by using multi-task training with self-supervised depth estimation
M Klingner, A Bar, T Fingscheidt
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
282020
Inspect, understand, overcome: a survey of practical methods for AI safety
S Houben, S Abrecht, M Akila, A Bär, F Brockherde, P Feifel, ...
Deep Neural Networks and Data for Automated Driving, 3-78, 2022
262022
SVDistNet: Self-supervised near-field distance estimation on surround view fisheye cameras
VR Kumar, M Klingner, S Yogamani, M Bach, S Milz, T Fingscheidt, ...
IEEE Transactions on Intelligent Transportation Systems, 2021
222021
Robust semantic segmentation by redundant networks with a layer-specific loss contribution and majority vote
A Bar, M Klingner, S Varghese, F Huger, P Schlicht, T Fingscheidt
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
162020
Unsupervised batchnorm adaptation (ubna): A domain adaptation method for semantic segmentation without using source domain representations
M Klingner, JA Termöhlen, J Ritterbach, T Fingscheidt
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022
132022
Class-Incremental Learning for Semantic Segmentation Re-Using Neither Old Data Nor Old Labels
M Klingner, A Bär, P Donn, T Fingscheidt
2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020
122020
Self-supervised domain mismatch estimation for autonomous perception
J Lohdefink, J Fehrling, M Klingner, F Huger, P Schlicht, NM Schmidt, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
112020
Online Performance Prediction of Perception DNNs by Multi-Task Learning With Depth Estimation
M Klingner, T Fingscheidt
IEEE Transactions on Intelligent Transportation Systems, 2021
62021
Detecting adversarial perturbations in multi-task perception
M Klingner, VR Kumar, S Yogamani, A Bär, T Fingscheidt
arXiv preprint arXiv:2203.01177, 2022
52022
DNN-Based Recognition of Pole-Like Objects in LiDAR Point Clouds
C Plachetka, J Fricke, M Klingner, T Fingscheidt
2021 IEEE International Intelligent Transportation Systems Conference (ITSC …, 2021
32021
Continual Unsupervised Domain Adaptation for Semantic Segmentation by Online Frequency Domain Style Transfer
JA Termöhlen, M Klingner, LJ Brettin, NM Schmidt, T Fingscheidt
2021 IEEE International Intelligent Transportation Systems Conference (ITSC …, 2021
32021
An Unsupervised Temporal Consistency (TC) Loss to Improve the Performance of Semantic Segmentation Networks
S Varghese, S Gujamagadi, M Klingner, N Kapoor, A Bar, JD Schneider, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
22021
Improving Online Performance Prediction for Semantic Segmentation
M Klingner, A Bar, M Mross, T Fingscheidt
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
22021
Improved DNN Robustness by Multi-task Training with an Auxiliary Self-Supervised Task
M Klingner, T Fingscheidt
Deep Neural Networks and Data for Automated Driving, 149, 2022
2022
Continual BatchNorm Adaptation (CBNA) for Semantic Segmentation
M Klingner, M Ayache, T Fingscheidt
arXiv preprint arXiv:2203.01074, 2022
2022
Performance Prediction for Semantic Segmentation by a Self-Supervised Image Reconstruction Decoder
A Bär, M Klingner, J Löhdefink, F Hüger, P Schlicht, T Fingscheidt
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
2022
On the Choice of Data for Efficient Training and Validation of End-to-End Driving Models
M Klingner, K Müller, M Mirzaie, J Breitenstein, JA Termöhlen, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
2022
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