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TUM Department of Informatics
Technical University of Munich

Technical University of Munich

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David Schubert

AlumniTechnical University of Munich

Department of Informatics
Informatics 9
Boltzmannstrasse 3
85748 Garching
Germany

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

Research

My research focuses on visual odometry and SLAM (see publications). This includes a visual and a visual-inertial odometry system for rolling-shutter cameras, the latter of which can be seen in the video above.

Datasets

Our visual-inertial stereo hardware setup has led to the publication of datasets which are well adopted by the research community. The two cameras of our setup can be operated in different shutter modes, which allows rolling/global-shutter comparisons.

Teaching

  • WS16/17 Computer Vision I: Variational Methods (Tutorial)
  • WS17/18 Diskrete Strukturen (Tutor groups)
  • SS18 Practical Course: GPU Programming in Computer Vision
  • WS18/19 Diskrete Strukturen (Tutor groups)
  • SS19 Computer Vision II: Multiple View Geometry (Tutorial)
  • SS20 Seminar: The Evolution of Motion Estimation and Real-time 3D Reconstruction
  • SS20 Practical Course: Vision-based Navigation
  • WS20/21 Practical Course: Vision-based Navigation
  • SS21 Practical Course: Vision-based Navigation
  • SS22 Seminar: Recent Advances in 3D Computer Vision

Publications


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Journal Articles
2020
[]Visual-Inertial Mapping with Non-Linear Factor Recovery (V. Usenko, N. Demmel, D. Schubert, J. Stueckler and D. Cremers), In IEEE Robotics and Automation Letters (RA-L) & Int. Conference on Intelligent Robotics and Automation (ICRA), IEEE, volume 5, 2020. ([arxiv]) [bibtex] [doi] [pdf]
Conference and Workshop Papers
2022
[] Gradient-SDF: A Semi-Implicit Surface Representation for 3D Reconstruction (C Sommer, L Sang, D Schubert and D Cremers), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.  [bibtex] [pdf]
2021
[]Square Root Marginalization for Sliding-Window Bundle Adjustment (N Demmel, D Schubert, C Sommer, D Cremers and V Usenko), In IEEE International Conference on Computer Vision (ICCV), 2021. ([project page]) [bibtex] [arXiv:2109.02182] [pdf]
2020
[]Efficient Derivative Computation for Cumulative B-Splines on Lie Groups (C. Sommer, V. Usenko, D. Schubert, N. Demmel and D. Cremers), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.  [bibtex] [doi] [arXiv:1911.08860] [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 Odometry With Rolling Shutter (D. Schubert, N. Demmel, V. Usenko, J. Stueckler and D. Cremers), In European Conference on Computer Vision (ECCV), 2018. ([supplementary][arxiv]) [bibtex] [pdf]Oral Presentation
[]The TUM VI Benchmark for Evaluating Visual-Inertial Odometry (D. Schubert, T. Goll, N. Demmel, V. Usenko, J. Stueckler and D. Cremers), In International Conference on Intelligent Robots and Systems (IROS), 2018. ([arxiv]) [bibtex] [pdf]
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Rechte Seite

Informatik IX
Chair of Computer Vision & Artificial Intelligence

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

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News

03.04.2022

In April 2022 Jürgen Sturm, Christian Kerl and Daniel Cremers were featured among the top 10 most influential scholars in robotics of the last decade.

31.03.2022

We have open PhD and postdoc positions! To apply, please use our application form.

08.03.2022

We have six papers accepted to CVPR 2022 in New Orleans!

31.01.2022

We have two papers accepted to ICRA 2022 - congrats to Lukas von Stumberg, Qing Cheng and Niclas Zeller!

05.12.2021
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