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Computer Vision Group
TUM School of Computation, Information and Technology
Technical University of Munich

Technical University of Munich



Qadeer Khan

PhD StudentTechnical University of Munich

School of Computation, Information and Technology
Informatics 9
Boltzmannstrasse 3
85748 Garching

Tel: +49-89-289-17750
Fax: +49-89-289-17757
Office: 02.09.060
Mail: qadeer.khan@tum.de


Offered Projects

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.

Ongoing Projects

  • Pseudo-Lidar Vehicle navigation.
  • Multi-agent vehicle control in unconstrained environments
  • Discrete Optimization with graphical neural networks
  • Economic load dispatch of power generation.

Completed Projects

  • Learning robust vehicle Control from multiple image [IDP, Idil Sülö]
  • Offline Reinforcement Learning for vehicle control. [IDP, Samuel Weber]
  • VentriloquistNet: Leveraging Speech Cues to Generate Naturalistic Talking Head Motions. [Master Thesis, Deepan Das]
  • 3D Spatial Motion Estimation of Image Pixels. [Guided Research, Tong Yan Chan]
  • Active Learning For Reducing The Labelling Effort in Semantic Segmentation. [Application Project, Mohab Ghanem]
  • Self-supervised Novel View Image Synthesis for Improving Performance of Driving Algorithms.[Master Thesis, Yiu Ting Tang]
  • Relative Pose Estimation using Novel View Synthesis for Relocalization.[Guided Research, Melis Öcal]
  • 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
[]Learning vision based autonomous lateral vehicle control without supervision (Q Khan, I Sülö, M Öcal and D Cremers), In Applied Intelligence, Springer, 2023. ([paper][github]) [bibtex] [video]
[]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]
[]Multi-Vehicle Trajectory Prediction at Intersections using State and Intention Information (D Zhu, Q Khan and D Cremers), In arXiv preprint, 2023.  [bibtex] [pdf]
Conference and Workshop Papers
[]Ventriloquist-Net: Leveraging Speech Cues for Emotive Talking Head Generation (D Das, Q Khan and D Cremers), In IEEE International Conference on Image Processing, 2022.  [bibtex]
[]Biologically Inspired Neural Path Finding (L Hang, Q Khan, V Tresp and D Cremers), In Brain Informatics, Springer International Publishing, 2022. ([code]) [bibtex]
[]Lateral Ego-Vehicle Control Without Supervision Using Point Clouds (F Müller, Q Khan and D Cremers), In Pattern Recognition and Artificial Intelligence, Springer International Publishing, 2022.  [bibtex] [pdf]
[]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]
[]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]
[]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]
[]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]
[]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]
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Informatik IX
Computer Vision Group

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

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CVPR 2023

We have six papers accepted to CVPR 2023.


NeurIPS 2022

We have two papers accepted to NeurIPS 2022.


WACV 2023

We have two papers accepted at WACV 2023.


Fulbright PULSE podcast on Prof. Cremers went online on Apple Podcasts and Spotify.


MCML Kick-Off

On July 27th, we are organizing the Kick-Off of the Munich Center for Machine Learning in the Bavarian Academy of Sciences.