• WS20/21: Practical course Learning For Self-Driving Cars and Intelligent Systems
• SS20: Practical course Learning For Self-Driving Cars and Intelligent Systems with Patrick Wenzel.
• WS19/20: Practical course Learning For Self-Driving Cars and Intelligent Systems with Yuesong Shen and Patrick Wenzel.
• SS19: Practical course Hands-on Deep Learning for Computer Vision and Biomedicine with Vladimir Golkov and Patrick Wenzel.

In case you are interested in doing an IDP, Guided Research, Bachelor/Master thesis, in the areas of Graphical neural networks, active learning, vehicle control feel free to send your application including resume and transcripts and a short description of the area of interest.

• Motion estimation of dynamic objects from images
• Unsupervised re-localization of image sequences
• Unsupervised multi-view image synthesis.

• Deep Active learning on Graphical networks for semantic segmentation.[Master Thesis, Viktor Drobnyi]
• Model Pruning for faster inference [Guided Research, Paul Ursulean]
• Self-Supervised Vehicle Control on Sparse 3D point clouds [Bachelor Thesis, Florian Müller]
• IMU based pose estimation using deep neural networks [IDP, Nicholas Gao]

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Journal Articles
2020
[]		GN-Net: The Gauss-Newton Loss for Multi-Weather Relocalization (L. von Stumberg, P. Wenzel, Q. Khan and D. Cremers), In IEEE Robotics and Automation Letters (RA-L), volume 5, 2020. ([arXiv][video][project page][supplementary]) [bibtex]
Conference and Workshop Papers
2021
[]		Self-Supervised Steering Angle Prediction for Vehicle Control Using Visual Odometry (Q. Khan, P. Wenzel and D. Cremers), In International Conference on Artificial Intelligence and Statistics (AISTATS), 2021. ([arXiv]) [bibtex]
2020
[]		4Seasons: A Cross-Season Dataset for Multi-Weather SLAM in Autonomous Driving (P. Wenzel, R. Wang, N. Yang, Q. Cheng, Q. Khan, L. von Stumberg, N. Zeller and D. Cremers), In Proceedings of the German Conference on Pattern Recognition (GCPR), 2020. ([project page][arXiv][video]) [bibtex] [pdf]
2019
[]		Towards Generalizing Sensorimotor Control Across Weather Conditions (Q. Khan, P. Wenzel, D. Cremers and L. Leal-Taixé), In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019. ([arXiv]) [bibtex] [pdf]
2018
[]		Modular Vehicle Control for Transferring Semantic Information Between Weather Conditions Using GANs (P. Wenzel, Q. Khan, D. Cremers and L. Leal-Taixé), In Conference on Robot Learning (CoRL), 2018. ([arXiv][videos][poster]) [bibtex] [pdf]
[]		q-Space Deep Learning for Alzheimer's Disease Diagnosis: Global Prediction and Weakly-Supervised Localization (V. Golkov, P. Swazinna, M. M. Schmitt, Q. A. Khan, C. M. W. Tax, M. Serahlazau, F. Pasa, F. Pfeiffer, G. J. Biessels, A. Leemans and D. Cremers), In International Society for Magnetic Resonance in Medicine (ISMRM) Annual Meeting, 2018.  [bibtex] [pdf]
2017
[]		Establishment of an interdisciplinary workflow of machine learning-based Radiomics in sarcoma patients (J.C. Peeken, C. Knie, V. Golkov, K. Kessel, F. Pasa, Q. Khan, M. Seroglazov, J. Kukačka, T. Goldberg, L. Richter, J. Reeb, B. Rost, F. Pfeiffer, D. Cremers, F. Nüsslin and S.E. Combs), In 23. Jahrestagung der Deutschen Gesellschaft für Radioonkologie (DEGRO), 2017.  [bibtex]