Matthias Rottmann

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 81

Top Topics

Semantic Segmentation

Top Venues

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)
Alexey Nekrasov, Rui Zhou, Miriam Ackermann, Alexander Hermans, Bastian Leibe, Matthias Rottmann
OoDIS: Anomaly Instance Segmentation Benchmark. CoRR (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)
Jialong Wu, Mirko Meuter, Markus Schoeler, Matthias Rottmann
SparseRadNet: Sparse Perception Neural Network on Subsampled Radar Data. CoRR (2024)
Edgar Heinert, Matthias Rottmann, Kira Maag, Karsten Kahl
Reducing Texture Bias of Deep Neural Networks via Edge Enhancing Diffusion. CoRR (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)
Lorenc Kapllani, Long Teng, Matthias Rottmann
Uncertainty quantification for deep learning-based schemes for solving high-dimensional backward stochastic differential equations. CoRR (2023)
Annika Mütze, Matthias Rottmann, Hanno Gottschalk
Semi-Supervised Domain Adaptation with CycleGAN Guided by Downstream Task Awareness. VISIGRAPP (5: VISAPP) (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)
Matthias Rottmann, Marco Reese
Automated Detection of Label Errors in Semantic Segmentation Datasets via Deep Learning and Uncertainty Quantification. 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)
Pascal Colling, Matthias Rottmann, Lutz Roese-Koerner, Hanno Gottschalk
Prediction Quality Meta Regression and Error Meta Classification for Segmented Lidar Point Clouds. Int. J. Artif. Intell. Tools 32 (5) (2023)
Jesus Espinoza-Valverde, Andreas Frommer, Gustavo Ramirez-Hidalgo, Matthias Rottmann
Coarsest-level improvements in multigrid for lattice QCD on large-scale computers. Comput. Phys. Commun. 292 (2023)
Robin Chan, Radin Dardashti, Meike Osinski, Matthias Rottmann, Dominik Brüggemann, Cilia Rücker, Peter Schlicht, Fabian Hüger, Nikol Rummel, Hanno Gottschalk
What should AI see? Using the public's opinion to determine the perception of an AI. AI Ethics 3 (4) (2023)
Antonia van Betteray, Matthias Rottmann, Karsten Kahl
MGiaD: Multigrid in all dimensions. Efficiency and robustness by weight sharing and coarsening in resolution and channel dimensions. ICCV (Workshops) (2023)
Julian Burghoff, Matthias Rottmann, Jill von Conta, Sebastian Schoenen, Andreas Witte, Hanno Gottschalk
ResBuilder: Automated Learning of Depth with Residual Structures. CoRR (2023)
Matthias Rottmann, Kira Maag, Mathis Peyron, Hanno Gottschalk, Natasa Krejic
Detection of Iterative Adversarial Attacks via Counter Attack. J. Optim. Theory Appl. 198 (3) (2023)
Kira Maag, Matthias Rottmann
False Negative Reduction in Semantic Segmentation Under Domain Shift Using Depth Estimation. VISIGRAPP (5: VISAPP) (2023)
Antonia van Betteray, Matthias Rottmann, Karsten Kahl
MGiaD: Multigrid in all dimensions. Efficiency and robustness by coarsening in resolution and channel dimensions. CoRR (2022)
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)
Robin Chan, Svenja Uhlemeyer, Matthias Rottmann, Hanno Gottschalk
Detecting and Learning the Unknown in Semantic Segmentation. CoRR (2022)
Annika Mütze, Matthias Rottmann, Hanno Gottschalk
Semi-supervised domain adaptation with CycleGAN guided by a downstream task loss. CoRR (2022)
Philipp Oberdiek, Gernot A. Fink, Matthias Rottmann
UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs. NeurIPS (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)
Matthias Rottmann, Marco Reese
Automated Detection of Label Errors in Semantic Segmentation Datasets via Deep Learning and Uncertainty Quantification. CoRR (2022)
Svenja Uhlemeyer, Matthias Rottmann, Hanno Gottschalk
Towards Unsupervised Open World Semantic Segmentation. CoRR (2022)
Kira Maag, Matthias Rottmann
False Negative Reduction in Semantic Segmentation under Domain Shift using Depth Estimation. CoRR (2022)
Philipp Oberdiek, Gernot A. Fink, Matthias Rottmann
UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs. CoRR (2022)
Jesus Espinoza-Valverde, Andreas Frommer, Gustavo Ramirez-Hidalgo, Matthias Rottmann
Coarsest-level improvements in multigrid for lattice QCD on large-scale computers. CoRR (2022)
Robin Chan, Radin Dardashti, Meike Osinski, Matthias Rottmann, Dominik Brüggemann, Cilia Rücker, Peter Schlicht, Fabian Hüger, Nikol Rummel, Hanno Gottschalk
What should AI see? Using the Public's Opinion to Determine the Perception of an AI. CoRR (2022)
Svenja Uhlemeyer, Matthias Rottmann, Hanno Gottschalk
Towards unsupervised open world semantic segmentation. UAI (2022)
Krzysztof Lis, Matthias Rottmann, Sina Honari, Pascal Fua, Mathieu Salzmann
AttEntropy: Segmenting Unknown Objects in Complex Scenes using the Spatial Attention Entropy of Semantic Segmentation Transformers. CoRR (2022)
Pascal Colling, Dennis Müller, Matthias Rottmann
HD Lane Map Generation Based on Trail Map Aggregation. IV (2022)
Julia Rosenzweig, Eduardo Brito, Hans-Ulrich Kobialka, Maram Akila, Nico M. Schmidt, Peter Schlicht, Jan David Schneider, Fabian Hüger, Matthias Rottmann, Sebastian Houben, Tim Wirtz
Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis. CoRR (2021)
Hanno Gottschalk, Matthias Rottmann, Maida Saltagic
Does Redundancy in AI Perception Systems Help to Test for Super-Human Automated Driving Performance? CoRR (2021)
Pascal Colling, Lutz Roese-Koerner, Hanno Gottschalk, Matthias Rottmann
MetaBox+: A New Region based Active Learning Method for Semantic Segmentation using Priority Maps. ICPRAM (2021)
Sebastian Houben, Stephanie Abrecht, Maram Akila, Andreas Bär, Felix Brockherde, Patrick Feifel, Tim Fingscheidt, Sujan Sai Gannamaneni, Seyed Eghbal Ghobadi, Ahmed Hammam, Anselm Haselhoff, Felix Hauser, Christian Heinzemann, Marco Hoffmann, Nikhil Kapoor, Falk Kappel, Marvin Klingner, Jan Kronenberger, Fabian Küppers, Jonas Löhdefink, Michael Mlynarski, Michael Mock, Firas Mualla, Svetlana Pavlitskaya, Maximilian Poretschkin, Alexander Pohl, Varun Ravi Kumar, Julia Rosenzweig, Matthias Rottmann, Stefan Rüping, Timo Sämann, Jan David Schneider, Elena Schulz, Gesina Schwalbe, Joachim Sicking, Toshika Srivastava, Serin Varghese, Michael Weber, Sebastian Wirkert, Tim Wirtz, Matthias Woehrle
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety. CoRR (2021)
Pascal Colling, Matthias Rottmann, Lutz Roese-Koerner, Hanno Gottschalk
False Positive Detection and Prediction Quality Estimation for LiDAR Point Cloud Segmentation. ICTAI (2021)
Julia Rosenzweig, Eduardo Brito, Hans-Ulrich Kobialka, Maram Akila, Nico M. Schmidt, Peter Schlicht, Jan David Schneider, Fabian Hüger, Matthias Rottmann, Sebastian Houben, Tim Wirtz
Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis. IV Workshops (2021)
Robin Chan, Krzysztof Lis, Svenja Uhlemeyer, Hermann Blum, Sina Honari, Roland Siegwart, Mathieu Salzmann, Pascal Fua, Matthias Rottmann
SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation. CoRR (2021)
Kamil Kowol, Matthias Rottmann, Stefan Bracke, Hanno Gottschalk
YOdar: Uncertainty-based Sensor Fusion for Vehicle Detection with Camera and Radar Sensors. ICAART (2) (2021)
Pascal Colling, Matthias Rottmann, Lutz Roese-Koerner, Hanno Gottschalk
False Positive Detection and Prediction Quality Estimation for LiDAR Point Cloud Segmentation. CoRR (2021)
Kira Maag, Matthias Rottmann, Serin Varghese, Fabian Hüger, Peter Schlicht, Hanno Gottschalk
Improving Video Instance Segmentation by Light-weight Temporal Uncertainty Estimates. IJCNN (2021)
Claudia Drygala, Matthias Rottmann, Hanno Gottschalk, Klaus Friedrichs, Thomas Kurbiel
Background-Foreground Segmentation for Interior Sensing in Automotive Industry. CoRR (2021)
Tobias Riedlinger, Matthias Rottmann, Marius Schubert, Hanno Gottschalk
Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors. CoRR (2021)
Robin Chan, Matthias Rottmann, Hanno Gottschalk
Entropy Maximization and Meta Classification for Out-of-Distribution Detection in Semantic Segmentation. ICCV (2021)
Andreas Frommer, Karsten Kahl, Francesco Knechtli, Matthias Rottmann, Artur Strebel, Ian Zwaan
A multigrid accelerated eigensolver for the Hermitian Wilson-Dirac operator in lattice QCD. Comput. Phys. Commun. 258 (2021)
Robin Chan, Krzysztof Lis, Svenja Uhlemeyer, Hermann Blum, Sina Honari, Roland Siegwart, Pascal Fua, Mathieu Salzmann, Matthias Rottmann
SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation. NeurIPS Datasets and Benchmarks (2021)
Marius Schubert, Karsten Kahl, Matthias Rottmann
MetaDetect: Uncertainty Quantification and Prediction Quality Estimates for Object Detection. IJCNN (2021)
Kira Maag, Matthias Rottmann, Fabian Hüger, Peter Schlicht, Hanno Gottschalk
Improving Video Instance Segmentation by Light-weight Temporal Uncertainty Estimates. CoRR (2020)
Hayk Asatryan, Hanno Gottschalk, Marieke Lippert, Matthias Rottmann
A Convenient Infinite Dimensional Framework for Generative Adversarial Learning. CoRR (2020)
Matthias Rottmann, Mathis Peyron, Natasa Krejic, Hanno Gottschalk
Detection of Iterative Adversarial Attacks via Counter Attack. CoRR (2020)
Matthias Rottmann, Pascal Colling, Thomas-Paul Hack, Robin Chan, Fabian Hüger, Peter Schlicht, Hanno Gottschalk
Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities. IJCNN (2020)
Kira Maag, Matthias Rottmann, Hanno Gottschalk
Time-Dynamic Estimates of the Reliability of Deep Semantic Segmentation Networks. ICTAI (2020)
Robin Chan, Matthias Rottmann, Fabian Hüger, Peter Schlicht, Hanno Gottschalk
Controlled False Negative Reduction of Minority Classes in Semantic Segmentation. IJCNN (2020)
Robin Chan, Matthias Rottmann, Hanno Gottschalk
Entropy Maximization and Meta Classification for Out-Of-Distribution Detection in Semantic Segmentation. CoRR (2020)
Pascal Colling, Lutz Roese-Koerner, Hanno Gottschalk, Matthias Rottmann
MetaBox+: A new Region Based Active Learning Method for Semantic Segmentation using Priority Maps. CoRR (2020)
Philipp Oberdiek, Matthias Rottmann, Gernot A. Fink
Detection and Retrieval of Out-of-Distribution Objects in Semantic Segmentation. CoRR (2020)
Matthias Rottmann, Kira Maag, Robin Chan, Fabian Hüger, Peter Schlicht, Hanno Gottschalk
Detection of False Positive and False Negative Samples in Semantic Segmentation. DATE (2020)
Philipp Oberdiek, Matthias Rottmann, Gernot A. Fink
Detection and Retrieval of Out-of-Distribution Objects in Semantic Segmentation. CVPR Workshops (2020)
Marius Schubert, Karsten Kahl, Matthias Rottmann
MetaDetect: Uncertainty Quantification and Prediction Quality Estimates for Object Detection. CoRR (2020)
Kamil Kowol, Matthias Rottmann, Stefan Bracke, Hanno Gottschalk
YOdar: Uncertainty-based Sensor Fusion for Vehicle Detection with Camera and Radar Sensors. CoRR (2020)
Robin Chan, Matthias Rottmann, Radin Dardashti, Fabian Hüger, Peter Schlicht, Hanno Gottschalk
The Ethical Dilemma When (Not) Setting up Cost-Based Decision Rules in Semantic Segmentation. CVPR Workshops (2019)
Matthias Rottmann, Marius Schubert
Uncertainty Measures and Prediction Quality Rating for the Semantic Segmentation of Nested Multi Resolution Street Scene Images. CoRR (2019)
Robin Chan, Matthias Rottmann, Fabian Hüger, Peter Schlicht, Hanno Gottschalk
MetaFusion: Controlled False-Negative Reduction of Minority Classes in Semantic Segmentation. CoRR (2019)
Robin Chan, Matthias Rottmann, Radin Dardashti, Fabian Hüger, Peter Schlicht, Hanno Gottschalk
The Ethical Dilemma when (not) Setting up Cost-based Decision Rules in Semantic Segmentation. 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)
Matthias Rottmann, Kira Maag, Robin Chan, Fabian Hüger, Peter Schlicht, Hanno Gottschalk
Detection of False Positive and False Negative Samples in Semantic Segmentation. CoRR (2019)
Andreas Behrend, Anton Dignös, Johann Gamper, Philip Schmiegelt, Hannes Voigt, Matthias Rottmann, Karsten Kahl
Period Index: A Learned 2D Hash Index for Range and Duration Queries. SSTD (2019)
Robin Chan, Matthias Rottmann, Fabian Hüger, Peter Schlicht, Hanno Gottschalk
Application of Decision Rules for Handling Class Imbalance in Semantic Segmentation. CoRR (2019)
Kira Maag, Matthias Rottmann, Hanno Gottschalk
Time-Dynamic Estimates of the Reliability of Deep Semantic Segmentation Networks. CoRR (2019)
Karsten Kahl, Matthias Rottmann
Least Angle Regression Coarsening in Bootstrap Algebraic Multigrid. SIAM J. Sci. Comput. 40 (6) (2018)
Matthias Rottmann, Karsten Kahl, Hanno Gottschalk
Deep Bayesian Active Semi-Supervised Learning. CoRR (2018)
Matthias Rottmann, Pascal Colling, Thomas-Paul Hack, Fabian Hüger, Peter Schlicht, Hanno Gottschalk
Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities. CoRR (2018)
Philipp Oberdiek, Matthias Rottmann, Hanno Gottschalk
Classification Uncertainty of Deep Neural Networks Based on Gradient Information. CoRR (2018)
Matthias Rottmann, Karsten Kahl, Hanno Gottschalk
Deep Bayesian Active Semi-Supervised Learning. ICMLA (2018)
Philipp Oberdiek, Matthias Rottmann, Hanno Gottschalk
Classification Uncertainty of Deep Neural Networks Based on Gradient Information. ANNPR (2018)
James J. Brannick, Andreas Frommer, Karsten Kahl, Björn Leder, Matthias Rottmann, Artur Strebel
Multigrid preconditioning for the overlap operator in lattice QCD. Numerische Mathematik 132 (3) (2016)
Andreas Frommer, Karsten Kahl, Stefan Krieg, Björn Leder, Matthias Rottmann
Adaptive Aggregation-Based Domain Decomposition Multigrid for the Lattice Wilson-Dirac Operator. SIAM J. Sci. Comput. 36 (4) (2014)