| 2026 | WACV | Temporal Object Captioning for Street Scene Videos from LiDAR Tracks. | Vignesh Gopinathan, Urs Zimmermann, Michael Arnold, Matthias Rottmann |
| 2026 | WACV | Can We Challenge Open-Vocabulary Object Detectors with Generated Content in Street Scenes? | Annika Mtze, Sadia Ilyas, Christian Drpelkus, Matthias Rottmann |
| 2025 | ECAI | LFA Applied to CNNs: Efficient Singular Value Decomposition of Convolutional Mappings by Local Fourier Analysis. | Antonia van Betteray, Matthias Rottmann, Karsten Kahl |
| 2025 | ECAI | Transferring Styles for Reduced Texture Bias and Improved Robustness in Semantic Segmentation Networks. | Ben Hamscher, Edgar Heinert, Annika Mtze, Kira Maag, Matthias Rottmann |
| 2025 | ECAI | On the Influence of Shape, Texture and Color for Learning Semantic Segmentation. | Annika Mtze, Natalie Grabowsky, Edgar Heinert, Matthias Rottmann, Hanno Gottschalk |
| 2025 | ICCV | TARS: Traffic-Aware Radar Scene Flow Estimation. | Jialong Wu, Marco Braun, Dominic Spata, Matthias Rottmann |
| 2025 | ICPRAM | Poly-MgNet: Polynomial Building Blocks in Multigrid-Inspired ResNets. | Antonia van Betteray, Matthias Rottmann, Karsten Kahl |
| 2025 | ICRA | OoDIS: Anomaly Instance Segmentation and Detection Benchmark. | Alexey Nekrasov, Rui Zhou, Miriam Ackermann, Alexander Hermans, Bastian Leibe, Matthias Rottmann |
| 2024 | BMVC | AttEntropy: On the Generalization Ability of Supervised Semantic Segmentation Transformers to New Objects in New Domains. | Krzysztof Baron-Lis, Matthias Rottmann, Annika Mtze, Sina Honari, Pascal Fua, Mathieu Salzmann |
| 2024 | BMVC | Uncertainty and Prediction Quality Estimation for Semantic Segmentation via Graph Neural Network. | Edgar Heinert, Stephan Tilgner, Timo Palm, Matthias Rottmann |
| 2024 | ECAI | Reducing Texture Bias of Deep Neural Networks via Edge Enhancing Diffusion. | Edgar Heinert, Matthias Rottmann, Kira Maag, Karsten Kahl |
| 2024 | ECCV | On the Potential of Open-Vocabulary Models for Object Detection in Unusual Street Scenes. | Sadia Ilyas, Ido Freeman, Matthias Rottmann |
| 2024 | ECCV | SparseRadNet: Sparse Perception Neural Network on Subsampled Radar Data. | Jialong Wu, Mirko Meuter, Markus Schoeler, Matthias Rottmann |
| 2024 | ICANN | ResBuilder: Automated Learning of Depth with Residual Structures. | Julian Burghoff, Matthias Rottmann, Jill von Conta, Sebastian Schoenen, Andreas Witte, Hanno Gottschalk |
| 2024 | WACV | Identifying Label Errors in Object Detection Datasets by Loss Inspection. | Marius Schubert, Tobias Riedlinger, Karsten Kahl, Daniel Krll, Sebastian Schoenen, Sinisa Segvic, Matthias Rottmann |
| 2024 | VISIGRAPP | Towards Rapid Prototyping and Comparability in Active Learning for Deep Object Detection. | Tobias Riedlinger, Marius Schubert, Karsten Kahl, Hanno Gottschalk, Matthias Rottmann |
| 2024 | VISIGRAPP | Deep Active Learning with Noisy Oracle in Object Detection. | Marius Schubert, Tobias Riedlinger, Karsten Kahl, Matthias Rottmann |
| 2023 | WACV | Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors. | Tobias Riedlinger, Matthias Rottmann, Marius Schubert, Hanno Gottschalk |
| 2023 | WACV | Automated Detection of Label Errors in Semantic Segmentation Datasets via Deep Learning and Uncertainty Quantification. | Matthias Rottmann, Marco Reese |
| 2022 | UAI | Towards unsupervised open world semantic segmentation. | Svenja Uhlemeyer, Matthias Rottmann, Hanno Gottschalk |
| 2021 | ICAART | YOdar: Uncertainty-based Sensor Fusion for Vehicle Detection with Camera and Radar Sensors. | Kamil Kowol, Matthias Rottmann, Stefan Bracke, Hanno Gottschalk |
| 2021 | ICCV | Entropy Maximization and Meta Classification for Out-of-Distribution Detection in Semantic Segmentation. | Robin Chan, Matthias Rottmann, Hanno Gottschalk |
| 2021 | ICPRAM | MetaBox+: A New Region based Active Learning Method for Semantic Segmentation using Priority Maps. | Pascal Colling, Lutz Roese-Koerner, Hanno Gottschalk, Matthias Rottmann |
| 2021 | IJCNN | Improving Video Instance Segmentation by Light-weight Temporal Uncertainty Estimates. | Kira Maag, Matthias Rottmann, Serin Varghese, Fabian Hger, Peter Schlicht, Hanno Gottschalk |
| 2021 | IJCNN | MetaDetect: Uncertainty Quantification and Prediction Quality Estimates for Object Detection. | Marius Schubert, Karsten Kahl, Matthias Rottmann |
| 2021 | ICTAI | False Positive Detection and Prediction Quality Estimation for LiDAR Point Cloud Segmentation. | Pascal Colling, Matthias Rottmann, Lutz Roese-Koerner, Hanno Gottschalk |
| 2020 | CVPR | Detection and Retrieval of Out-of-Distribution Objects in Semantic Segmentation. | Philipp Oberdiek, Matthias Rottmann, Gernot A. Fink |
| 2020 | DATE | Detection of False Positive and False Negative Samples in Semantic Segmentation. | Matthias Rottmann, Kira Maag, Robin Chan, Fabian Hger, Peter Schlicht, Hanno Gottschalk |
| 2020 | IJCNN | Controlled False Negative Reduction of Minority Classes in Semantic Segmentation. | Robin Chan, Matthias Rottmann, Fabian Hger, Peter Schlicht, Hanno Gottschalk |
| 2020 | IJCNN | Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities. | Matthias Rottmann, Pascal Colling, Thomas-Paul Hack, Robin Chan, Fabian Hger, Peter Schlicht, Hanno Gottschalk |
| 2020 | ICTAI | Time-Dynamic Estimates of the Reliability of Deep Semantic Segmentation Networks. | Kira Maag, Matthias Rottmann, Hanno Gottschalk |
| 2019 | CVPR | The Ethical Dilemma When (Not) Setting up Cost-Based Decision Rules in Semantic Segmentation. | Robin Chan, Matthias Rottmann, Radin Dardashti, Fabian Hger, Peter Schlicht, Hanno Gottschalk |
| 2019 | CVPR | Uncertainty Measures and Prediction Quality Rating for the Semantic Segmentation of Nested Multi Resolution Street Scene Images. | Matthias Rottmann, Marius Schubert |
| 2018 | ICMLA | Deep Bayesian Active Semi-Supervised Learning. | Matthias Rottmann, Karsten Kahl, Hanno Gottschalk |