Timo Kaiser
Leibniz Universität Hannover
eNIFE
Schneiderberg 32
30167 Hannover
Germany
phone: +49 511 762-19504
fax: +49 511 762-5333
office location: room 239
 

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.

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
  • 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
  • Timo Kaiser, Christoph Reinders, Bodo Rosenhahn
    Compensation Learning in Semantic Segmentation
    Computer Vision and Pattern Recognition Workshops (CVPRW) , June 2023
  • Timo Kaiser, Lukas Ehmann, Christoph Reinders, Bodo Rosenhahn
    Blind Knowledge Distillation for Robust Image Classification
    arXiv, arXiv, November 2022
  • 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
  • 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