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

Technical University of Munich

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Lukas von Stumberg

PhD Student

Technical University of Munich

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

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

Find me on Google Scholar Linkedin GitHub

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

DM-VIO: Delayed Marginalization Visual-Inertial Odometry

An open-source visual-inertial odometry system with state-of-the art results. See https://github.com/lukasvst/dm-vio

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
2022
[]DM-VIO: Delayed Marginalization Visual-Inertial Odometry (L. von Stumberg and D. Cremers), In IEEE Robotics and Automation Letters (RA-L) & International Conference on Robotics and Automation (ICRA), volume 7, 2022. ([arXiv][video][project page][supplementary][code]) [bibtex] [doi]
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
[]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]
[]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]
[]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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Informatik IX
Computer Vision Group

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

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News

15.10.2022

NeurIPS 2022

We have two papers accepted to NeurIPS 2022.

15.10.2022

WACV 2023

We have two papers accepted at WACV 2023.

31.08.2022

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

17.07.2022

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.

17.07.2022

AI Symposium

On July 22nd 2022, we are organizing a Symposium on AI within the Technology Forum of the Bavarian Academy of Sciences.

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