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Technical University of Munich

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Lukas von Stumberg

PhD Student

Technical University of Munich

Department of Informatics
Informatics 9
Boltzmannstrasse 3
85748 Garching
Germany

Fax: +49-89-289-17757
Office: 
Mail: stumberg@in.tum.de

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Research Interests

My research interests are visual and visual-inertial SLAM, robotics, and 3D reconstruction. I like to apply both traditional methods and deep learning.

Selected Projects

LM-Reloc: Levenberg-Marquardt Based Direct Visual Relocalization

As a follow-up of our previous work GN-Net, LM-Reloc boosts the performance of direct image alignment for relocalization using a novel loss formulation, and a pose estimation network.

GN-Net: The Gauss-Newton Loss for Multi-Weather Relocalization

Using our novel Gauss-Newton loss we improve the robustness of direct methods against strong illumination changes and bad initializations. This allows us to accurately relocalize between different weathers. Project Page



VI-DSO: Direct Sparse Visual-Inertial Odometry using Dynamic Marginalization

In my Master thesis on direct visual-inertial odometry we demonstrate state-of-the-art performance on the EuRoC dataset. Project Page



From Monocular SLAM to Autonomous Drone Exploration

In my Bachelor thesis I have used LSD-SLAM to explore an unknown environment with an autonomous drone.


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Book Chapters
2020
[]TUM Flyers: Vision—Based MAV Navigation for Systematic Inspection of Structures (V. Usenko, L. von Stumberg, J. Stückler and D. Cremers), Chapter in Bringing Innovative Robotic Technologies from Research Labs to Industrial End-users (F. Caccavale, C. Ott, B. Winkler, Z. Taylor, eds.), Springer International Publishing, 2020.  [bibtex] [doi]
2019
[]A Review and Quantitative Evaluation of Direct Visual–Inertial Odometry (L. von Stumberg, V. Usenko and D. Cremers), Chapter in Multimodal Scene Understanding (M. Yang, B. Rosenhahn, V. Murino, eds.), Academic Press, 2019.  [bibtex] [doi]
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]
2018
[]Omnidirectional DSO: Direct Sparse Odometry with Fisheye Cameras (H. Matsuki, L. von Stumberg, V. Usenko, J. Stueckler and D. Cremers), In IEEE Robotics and Automation Letters & Int. Conference on Intelligent Robots and Systems (IROS), IEEE, 2018. ([arxiv]) [bibtex] [pdf]
Conference and Workshop Papers
2021
[]MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera (F. Wimbauer, N. Yang, L. von Stumberg, N. Zeller and D Cremers), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. ([project page]) [bibtex] [arXiv:2011.11814]
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]
[]LM-Reloc: Levenberg-Marquardt Based Direct Visual Relocalization (L. von Stumberg, P. Wenzel, N. Yang and D. Cremers), In International Conference on 3D Vision (3DV), 2020. ([arXiv][project page][video][supplementary][poster]) [bibtex]
[]D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry (N. Yang, L. von Stumberg, R. Wang and D. Cremers), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.  [bibtex] [arXiv:2003.01060] [pdf]Oral Presentation
2019
[]Rolling-Shutter Modelling for Visual-Inertial Odometry (D. Schubert, N. Demmel, L. von Stumberg, V. Usenko and D. Cremers), In International Conference on Intelligent Robots and Systems (IROS), 2019. ([arxiv]) [bibtex] [pdf]
2018
[]Direct Sparse Visual-Inertial Odometry using Dynamic Marginalization (L. von Stumberg, V. Usenko and D. Cremers), In International Conference on Robotics and Automation (ICRA), 2018. ([supplementary][video][arxiv]) [bibtex] [pdf]
2017
[]Real-Time Trajectory Replanning for MAVs using Uniform B-splines and a 3D Circular Buffer (V. Usenko, L. von Stumberg, A. Pangercic and D. Cremers), In International Conference on Intelligent Robots and Systems (IROS), 2017. ([arxiv]) [bibtex] [pdf]Best Paper Award - Finalist (link)
[]From Monocular SLAM to Autonomous Drone Exploration (L. von Stumberg, V. Usenko, J. Engel, J. Stueckler and D. Cremers), In European Conference on Mobile Robots (ECMR), 2017.  [bibtex] [pdf]
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News

04.06.2021

Bernt Schiele (Max Planck Institute for Informatics) will give a talk in the TUM AI lecture series on June 10th, 3pm! Livestream

05.05.2021
French-German Machine Learning Symposium

French-German Machine Learning Symposium

The French-German Machine Learning Symposium aims to strengthen interactions and inspire collaborations between both countries. We invited some of the leading ML researchers from France and Germany to this two-day symposium to give a glimpse into their research, and engage in discussions on the future of machine learning and how to strengthen research collaborations in ML between France and Germany.

The list of speakers includes Yann LeCun, Cordelia Schmid, Jean-Bernard Lasserre, Bernhard Schölkopf, and many more! For the full program please visit the webpage.

03.05.2021

Ron Kimmel (Technion - Israel Institute of Technology) will give a talk in the TUM AI lecture series on May 6th, 3pm! Livestream

23.04.2021

4Seasons Dataset: We have released a novel dataset for benchmarking multi-weather SLAM in autonomous driving.

19.04.2021

Hao Li (Pinscreen) will give a talk in the TUM AI lecture series on April 22nd, 8pm! Livestream

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