Institut für Informationsverarbeitung (TNT)

Timo Kaiser studied Mechatronics at Leibniz Universität Hannover. During his B. Sc. studies he focussed on Robotics. During his M. Sc. studies he focussed on digital image processing. In his master thesis "Multi-Objekt Tracking mittels eines Ende-zu-Ende Trainings" the multiple people tracking problem is modeled and optimized as a Conditional Random Field. He passed the Master's Examination in march 2020 and received his M. Sc. degree.

Since Mai 2020 he is working towards his Dr.-Ing. at the Institut für Informationsverarbeitung (TNT). His main research interests include object detection, multiple object tracking and person re-identification.

Publications

Show selected publications only

Timo Kaiser, Ulman Vladimir, Bodo Rosenhahn,
CHOTA: A Higher Order Accuracy Metric for Cell Tracking
European Conference on Computer Vision Workshops (ECCVW), Springer, October 2024
(pdfGitHub) BibTeX
Patrick Glandorf*, Timo Kaiser*, Bodo Rosenhahn, (*contributed equally)
HyperSparse Neural Networks: Shifting Exploration to Exploitation through Adaptive Regularization
International Conference on Computer Vision Workshops (ICCVW), October 2023
(pdf, pdfarXiv.org) BibTeX
Timo Kaiser, Christoph Reinders, Bodo Rosenhahn
Compensation Learning in Semantic Segmentation
Computer Vision and Pattern Recognition Workshops (CVPRW) , June 2023
(pdf, pdfGitHub, arXiv.org) BibTeX
Timo Kaiser, Lukas Ehmann, Christoph Reinders, Bodo Rosenhahn
Blind Knowledge Distillation for Robust Image Classification
arXiv, arXiv, November 2022
(pdfarXiv.org) BibTeX
Andrea Hornakova*, Timo Kaiser*, Michal Rolinek, Bodo Rosenhahn, Paul Swoboda, Roberto Henschel, (* equal contribution)
Making Higher Order MOT Scalable: An Efficient Approximate Solver for Lifted Disjoint Paths
International Conference on Computer Vision (ICCV), IEEE, October 2021
(pdf, pdfarXiv.org) BibTeX
Andrea Hornakova*, Timo Kaiser*, Bodo Rosenhahn, Paul Swoboda, Roberto Henschel, (* equal contribution)
Higher Order Multiple Object Tracking for Crowded Scenes
Computer Vision and Pattern Recognition Workshops (CVPRW) , June 2021
(pdfPDF, GitHub, arXiv.org) BibTeX