| 2026 | ICAART | VideoGAN-Based Trajectory Proposal for Automated Vehicles. | Annajoyce Mariani, Kira Maag, Hanno Gottschalk |
| 2025 | CVPR | Out-of-Distribution Segmentation in Autonomous Driving: Problems and State of the Art. | Youssef Shoeb, Azarm Nowzad, Hanno Gottschalk |
| 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 | ESANN | Robust Evolutionary Multi-Objective Neural Architecture Search for Reinforcement Learning (EMNAS-RL). | Nihal Acharya Adde, Alexandra Gianzina, Hanno Gottschalk, Andreas Ebert |
| 2025 | VISIGRAPP | MetaToken: Detecting Hallucination in Image Descriptions by Meta Classification. | Laura Fieback, Jakob Spiegelberg, Hanno Gottschalk |
| 2025 | VISIGRAPP | Segment-Level Road Obstacle Detection Using Visual Foundation Model Priors and Likelihood Ratios. | Youssef Shoeb, Nazir Nayal, Azarm Nowzad, Fatma Gney, Hanno Gottschalk |
| 2024 | ACCV | Strong but Simple: A Baseline for Domain Generalized Dense Perception by CLIP-Based Transfer Learning. | Christoph Hmmer, Manuel Schwonberg, Liangwei Zhou, Hu Cao, Alois Knoll, Hanno Gottschalk |
| 2024 | BMVC | A Study on Unsupervised Domain Adaptation for Semantic Segmentation in the Era of Vision-Language Models. | Manuel Schwonberg, Claus Werner, Hanno Gottschalk, Carsten Meyer |
| 2024 | BMVC | Unsupervised Class Incremental Learning using Empty Classes. | Svenja Uhlemeyer, Julian Lienen, Youssef Shoeb, Eyke Hllermeier, Hanno Gottschalk |
| 2024 | ECCV | AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous Driving. | Daniel Bogdoll, Iramm Hamdard, Lukas Namgyu Rler, Felix Geisler, Muhammed Bayram, Felix Wang, Jan Imhof, Miguel de Campos, Anushervon Tabarov, Yitian Yang, Martin Gontscharow, Hanno Gottschalk, J. Marius Zllner |
| 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 | Have We Ever Encountered This Before? Retrieving Out-of-Distribution Road Obstacles from Driving Scenes. | Youssef Shoeb, Robin Chan, Gesina Schwalbe, Azarm Nowzad, Fatma Gney, Hanno Gottschalk |
| 2024 | VISIGRAPP | Towards Rapid Prototyping and Comparability in Active Learning for Deep Object Detection. | Tobias Riedlinger, Marius Schubert, Karsten Kahl, Hanno Gottschalk, Matthias Rottmann |
| 2023 | ICANN | Risk Stratification of Malignant Melanoma Using Neural Networks. | Julian Burghoff, Leonhard Ackermann, Younes Salahdine, Veronika Bram, Katharina Wunderlich, Julius Balkenhol, Thomas Dirschka, Hanno Gottschalk |
| 2023 | ICANN | Who Breaks Early, Looses: Goal Oriented Training of Deep Neural Networks Based on Port Hamiltonian Dynamics. | Julian Burghoff, Marc Heinrich Monells, Hanno Gottschalk |
| 2023 | IJCNN | LU-Net: Invertible Neural Networks Based on Matrix Factorization. | Robin Chan, Sarina Penquitt, Hanno Gottschalk |
| 2023 | WACV | Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors. | Tobias Riedlinger, Matthias Rottmann, Marius Schubert, Hanno Gottschalk |
| 2022 | ACCV | Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects. | Kira Maag, Robin Chan, Svenja Uhlemeyer, Kamil Kowol, Hanno Gottschalk |
| 2022 | CHIRA | A-Eye: Driving with the Eyes of AI for Corner Case Generation. | Kamil Kowol, Stefan Bracke, Hanno Gottschalk |
| 2022 | CHIRA | survAIval: Survival Analysis with the Eyes of AI. | Kamil Kowol, Stefan Bracke, Hanno Gottschalk |
| 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 | ICTAI | False Positive Detection and Prediction Quality Estimation for LiDAR Point Cloud Segmentation. | Pascal Colling, Matthias Rottmann, Lutz Roese-Koerner, Hanno Gottschalk |
| 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 |
| 2018 | ICMLA | Deep Bayesian Active Semi-Supervised Learning. | Matthias Rottmann, Karsten Kahl, Hanno Gottschalk |