Friedhelm Hamann
Photo: SCIoI
Friedhelm Hamann is an electrical engineer and computer-vision researcher with a background in visual perception, event-based vision, and robotics.
He joined SCIoI as a doctoral researcher in October 2021 under the supervision of Prof. Guillermo Gallego.
Friedhelm received his B.Sc. from the University of Rostock and his M.Sc. in Electrical Engineering and Information Technology from RWTH Aachen University.
At SCIoI, he worked on event-based vision for robotic perception. His research focused on using bio-inspired event cameras to analyze dynamic scenes and support the behavioral analysis of animals. His doctoral thesis (see below), examines how event-based vision can be used to extract and interpret information from rapidly changing environments.
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Hamann, F., Mededovic, E., Gülhan, F., Wu, Y., Stegmaier, J., He, J., Wang, Y., Zhang, K., Li, L., Jiao, L., Ma, M., Huang, H., Yan, Y., Ren, H., Lin, X., Huang, Y., Cheng, B., Lee, S. H., Ham, G. S., … Gallego, G. (2025). SIS-Challenge: Event-Based Spatio-Temporal Instance Segmentation Challenge at the CVPR 2025 Event-Based Vision Workshop. 2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 4734–4742. https://doi.org/10.1109/ICCVW69036.2025.00491
Guo, S., Hamann, F., & Gallego, G. (2025). Unsupervised Joint Learning of Optical Flow and Intensity with Event Cameras. 2025 IEEE/CVF International Conference on Computer Vision (ICCV), 7980–7989. https://doi.org/10.1109/ICCV51701.2025.00748
Hamann, F., Gehrig, D., Febryanto, F., Daniilidis, K., & Gallego, G. (2025). ETAP: Event-based Tracking of Any Point. 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 27186–27196. https://doi.org/10.1109/CVPR52734.2025.02532
Wang, Z., Hamann, F., Chaney, K., Jiang, W., Gallego, G., & Daniilidis, K. (2025). Event-Based Continuous Color Video Decompression from Single Frames. 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 4968–4978. https://doi.org/10.1109/CVPRW67362.2025.00490
Hamann, F., Ghosh, S., Juárez Martínez, I., Hart, T., Kacelnik, A., & Gallego, G. (2025). Fourier‐Based Action Recognition for Wildlife Behavior Quantification with Event Cameras. Advanced Intelligent Systems, 7(2), 2400353. https://doi.org/10.1002/aisy.202400353
Hamann, F., Wang, Z., Asmanis, I., Chaney, K., Gallego, G., & Daniilidis, K. (2025). Motion-Prior Contrast Maximization for Dense Continuous-Time Motion Estimation. In A. Leonardis, E. Ricci, S. Roth, O. Russakovsky, T. Sattler, & G. Varol (Eds.), Computer Vision – ECCV 2024 (pp. 18–37). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-72646-0_2
Hamann, F., Li, H., Mieske, P., Lewejohann, L., & Gallego, G. (2025). MouseSIS: A Frames-and-Events Dataset for Space-Time Instance Segmentation of Mice. In A. Del Bue, C. Canton, J. Pont-Tuset, & T. Tommasi (Eds.), Computer Vision – ECCV 2024 Workshops (pp. 156–173). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-92460-6_10
Hamann, F., Ghosh, S., Martínez, I. J., Hart, T., Kacelnik, A., & Gallego, G. (2024). Low-power, Continuous Remote Behavioral Localization with Event Cameras. 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 18612–18621. https://doi.org/10.1109/CVPR52733.2024.01761
Shiba, S., Hamann, F., Aoki, Y., & Gallego, G. (2024). Event-Based Background-Oriented Schlieren. IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(4), 2011–2026. https://doi.org/10.1109/TPAMI.2023.3328188
Hamann, F., & Gallego, G. (2022). Stereo Co-capture System for Recording and Tracking Fish with Frame- and Event Cameras [Poster]. Visual observation and analysis of Vertebrate And Insect Behavior (VAIB) Workshop at the 26th International Conference on Pattern Recognition (ICPR). https://doi.org/10.48550/arXiv.2207.07332
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