Looking for Hiwis for various tasks in Computer Vision, Deep Learning and general data science-related fields. Background in Python necessary and familiarity with ML or DL a plus. Drop me a mail!
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
- 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.
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, Andreas Zell. "Fast Future Frame Prediction for Region of Interest Proposals on UAVs" (2022, preprint) |
[2] | Benjamin Kiefer*, David Ott* and Andreas Zell. "Leveraging Synthetic Data in Object Detection on Unmanned Aerial Vehicles", 2022 26th International Conference on Pattern Recognition (ICPR). (*equal contribution) |
[3] | L. A. Varga*, B. Kiefer*, M. Messmer*, and A. 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), January 2022, pp. 2260–2270. (*equal contribution) |
[4] | Martin Meßmer*, Benjamin Kiefer* and Andreas Zell. "Gaining Scale Invariance in UAV Bird's Eye View Object Detection by Adaptive Resizing" , 2022 26th International Conference on Pattern Recognition (ICPR). (*equal contribution) |
[5] | B. Kiefer*, M. Messmer* and A. Zell, "Diminishing Domain Bias by Leveraging Domain Labels in Object Detection on UAVs," 2021 20th International Conference on Advanced Robotics (ICAR), 2021, pp. 523-530, doi: 10.1109/ICAR53236.2021.9659357. (*equal contribution) |