Technical University of Munich

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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
2020
[]		Distributed Photometric Bundle Adjustment (N Demmel, M Gao, E Laude, T Wu and D Cremers), In International Conference on 3D Vision (3DV), 2020. (to appear) [bibtex]Oral Presentation
[]		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
[]		The Double Sphere Camera Model (V. Usenko, N. Demmel and D. Cremers), In Proc. of the Int. Conference on 3D Vision (3DV), 2018. ([arxiv]) [bibtex] [arXiv:1807.08957] [pdf]
[]		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
[]		LDSO: Direct Sparse Odometry with Loop Closure (X. Gao, R. Wang, N. Demmel and D. Cremers), In International Conference on Intelligent Robots and Systems (IROS), 2018. ([arxiv][video][code][project]) [bibtex]
[]		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]
2015
[]		Interactive Multi-label Segmentation of RGB-D Images (J. Diebold, N. Demmel, C. Hazirbas, M. Möller and D. Cremers), In Scale Space and Variational Methods in Computer Vision (SSVM), 2015. ([code]) [bibtex] [doi] [pdf]
2010
[]		Becoming action-aware through reasoning about logged plan execution traces (L Mösenlechner, N Demmel and M Beetz), In International Conference on Intelligent Robots and Systems (IROS), 2010.  [bibtex] [pdf]

Check out the projects I'm involved in:

• Distributed Photometric Bundle Adjustment
• Efficient Derivative Computation for Cumulative B-Splines on Lie Groups
• Rolling Shutter Dataset
• Basalt: Visual-Inertial Mapping with Non-Linear Factor Recovery
• TUMVI Dataset for Visual Inertial Odometry
• LDSO - Direct Sparse Odometry with Loop Closure
• Double Sphere Camera Model
• Photometric Calibration

If you are interested in doing a Bachelor Thesis, Master Thesis, Interdisciplinary Project (IDP) or Guided Research in the field of SLAM, Visual Odometry, 3D Reconstruction, or Sensor fusion, feel free to contact me via email. Please include your recent transcript and a brief CV, so I know a bit about your background and courses taken. Depending on the research project, some experience with C++ and Computer Vision is usually required.

• WS20: Practical course Vision Based Navigation together with David Schubert.
• SS20: Practical course Vision Based Navigation together with Dr. Vladyslav Usenko and David Schubert.
• WS19: Practical course Vision Based Navigation together with Dr. Vladyslav Usenko.
• SS19: Practical course Vision Based Navigation together with Dr. Vladyslav Usenko. Awarded by the department as <color #ed1c24>best practical course 2018/19</color>.
• WS18/19: Practical course Vision Based Navigation together with Dr. Vladyslav Usenko. Awarded by the department as <color #ed1c24>best practical course 2018/19</color>.
• SS18: Tutorial for Computer Vision II: Multiple View Geometry together with Marvin Eisenberger. Lecturer: Prof. Dr. Daniel Cremers.
• WS17/18: Tutorial for Computer Vision I: Variational Methods together with Christiane Sommer. Lecturer: Dr. Yvain Queau.

Previously completed student projects include:

• Co-supervision (with Nan Yang, Lukas Köstler): Rémi Piau, "Toward Fast Deep Visual Place Recognition", Internship, August 2020. slides
• Co-supervision (with Dr. Vladyslav Usenko): Tim Stricker, "Efficient Techniques for Accurate Visual Place Recognition", Master Thesis, June 2020. thesis slides
• Supervision: Simon Klenk, "Photometric Bundle Adjustment for Globally Consistent Mapping", Master Thesis, June 2020. thesis slides
• Co-supervision (with Dr. Vladyslav Usenko): Pak Hong Chui, "Visual-Inertial Simultaneous Localization and Mapping with Multiple Cameras", Master Thesis, April 2020. thesis slides
• Co-supervision (with Emanuel Laude): Florian Hofherr, "Joint Optimization of Pose And Depth Using a Prox-Linear Approach", Master Thesis, December 2019. thesis slides
• Co-supervision (with Jens Harnisch, Infineon Technologies AG): Abdul Hannan Khan, "Face Recognition with a 3D Camera On an Embedded Processor", Master Thesis, November 2019. thesis slides
• Supervision (with Tim Mehling): Pablo Rodríguez Palafox, "Local Tracking and Mapping for Direct Visual SLAM", Master Thesis, October 2019. thesis slides
• Co-supervision (with Dr. Ulrich Klank, Magazino GmbH): Kanstantsin Tkachuk, "3D Scene Reconstruction for 2D Object Recognition", Bachelor Thesis, September 2019. thesis slides
• Supervision (with Prof. Dr. Jörg Stückler): Anton Troynikov, "Photometric Odometry for Dynamic Objects", Master Thesis, April 2019. thesis slides Blog
• Supervision: Maurice Hermwille, "Vignette Calibration for Fisheye Lenses", Master Thesis, September 2018. thesis slides
• Co-Supervision (with Dr. Tao Wu, Emanuel Laude): Zhongnan Qu, "Efficient Optimization for Robust Bundle Adjustment", Master Thesis, March 2018. thesis slides