Organizing the "1st Workshop on Maritime Computer Vision", featuring paper submissions, challenges and keynotes. Check it out at https://seadronessee.cs.uni-tuebingen.de/wacv23.
https://seadronessee.cs.uni-tuebingen.de/wacv23
Benjamin Kiefer
Background
Since 2019
PhD student at the Department of Cognitive Systems, University of Tübingen
2016-2019
M. Sc. Mathematics, University of Tübingen
2013 - 2016
B. Sc. Mathematics, University of Tübingen
Research Interests
Currently, I'm working on Deep Learning methods for Object Detection. More specifially, I try to improve Object Detectors by means of freely available meta/environmental data. This meta data helps object detectors be more robust.
Teaching Assistantships
- Artifical Intelligence (Winter 2022)
- Introduction to Neural Networks (Summer 2022)
- Proseminar: Topics in Deep Neural Networks (Winter 2021)
- Team Project: Developing a Web-based Evaluation Application for Deep Neural Network Tasks (Summer 2021)
- Einführung in die technische Informatik (Winter 2020)
- Mathematik II (Summer 2020)
- Deep Neural Networks (Winter 2019)
Avalon Project
I'm part of the Avalon project. This project's goal is to build autonomous vision-based AIs aboard a UAV to assist in maritime emergencies at north sea and baltic sea.
Generating Synthetic Data for UAV scenarios via DeepGTAV
With ever more realistic simulations, we can generate data synthetically to augment or even replace real data entirely. For this reason, jointly with David Ott, we adapted and improved the tool DeepGTAV to work for UAV scenarios. If you are looking for the synthetically generated object detection data for UAV scenarios, find it here. Find the tool here.
SeaDronesSee Benchmark
We created an object detection and tracking benchmark for the use case of maritime search and rescue. Find it here or more information on the corresponding Github repository.
Neuro Meeting - Paper reading club
The Neuro meeting is a kind of paper reading club, which meets roughly every two weeks to discuss research and applications all kinds of foundations and novelties of neural networks. The central goal of this group is to broaden the horizon and keep an overview over this fast-paced field.
See a list of proposed and past topics at
https://cloud.cs.uni-tuebingen.de/index.php/s/a2gXdMG39cYFJbP
If you are interested to listen to or hold a talk or join regularly just drop me a mail.
Supervised Theses
2021 | Bachelor thesis | Accelerating DNN Training Using Weight Extrapolation |
2021 | Bachelor thesis | Maritime Anomaly Detection Using Autoencoders |
2020 | Bachelor thesis | Domain Adaptation for Object Detection on UAVs |
2020 | Bachelor thesis | Sampling Useful Synthetic Data for UAV Object Detection |
Publications
[1] | Benjamin Kiefer, Yitong Quan, Andreas Zell; Memory Maps for Video Object Detection and Tracking on UAVs [arxiv] |
[2] | Benjamin Kiefer, et al. 1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Workshops, 2023 [arxiv, cvf] |
[3] | Timon Höfer, Benjamin Kiefer, Martin Messmer, Andreas Zell; HyperPosePDF - Hypernetworks Predicting the Probability Distribution on SO(3). In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023, pp. 2369-2379 [cvf] |
[4] | Benjamin Kiefer, Andreas Zell. "Fast Region of Interest Proposals on Maritime UAVs" (2022, accepted for publication at ICRA 2023) [arxiv] |
[5] | Benjamin Kiefer*, David Ott*, and Andreas Zell. Leveraging synthetic data in object detection on unmanned aerial vehicles. In 2022 26th International Conference on Pattern Recognition (ICPR), pages 3564--3571, 2022. (*equal contribution) [ieee, arxiv] |
[6] | Leon Amadeus Varga*, Benjamin Kiefer*, Martin Messmer*, and Andreas Zell. SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), pages 2260--2270, January 2022. (*equal contribution) [ieee, cvf, arxiv] |
[7] | Martin Messmer*, Benjamin Kiefer*, and Andreas Zell. Gaining scale invariance in uav bird’s eye view object detection by adaptive resizing. In 2022 26th International Conference on Pattern Recognition (ICPR), pages 3588--3594, 2022 (*equal contribution) [ieee, arxiv] |
[8] | Benjamin Kiefer*, Martin Messmer*, and Andreas Zell. Diminishing Domain Bias by Leveraging Domain Labels in Object Detection on UAVs. In 2021 20th International Conference on Advanced Robotics (ICAR), pages 523--530, December 2021. (*equal contribution) [ieee, arxiv] |
Reviews
Reviewed for:
- ICIP 2022
- ICPR 2022
- ECCV 2022
- WACV 2023
- ICRA 2023
- CVPR 2023