no code implementations • 20 Feb 2024 • Christian Schuessler, Wenxuan Zhang, Johanna Bräunig, Marcel Hoffmann, Michael Stelzig, Martin Vossiek
This emphasizes the practicality of our methodology in overcoming data scarcity challenges and advancing the field of automatic gesture recognition in VR and HCI applications.
1 code implementation • 19 Oct 2023 • Marcel Hoffmann, Lukas Galke, Ansgar Scherp
We study the problem of lifelong graph learning in an open-world scenario, where a model needs to deal with new tasks and potentially unknown classes.
no code implementations • 1 Sep 2023 • Marcel Hoffmann, Sandro Braun, Oliver Sura, Michael Stelzig, Christian Schüßler, Knut Graichen, Martin Vossiek
This paper presents an approach to automatically annotate automotive radar data with AI-segmented aerial camera images.
1 code implementation • 16 Jun 2023 • Christian Schuessler, Marcel Hoffmann, Martin Vossiek
The key to this performance is that the DNN is trained using realistic simulation data that perfectly mimic a given sparse antenna radar array hardware as the input.
no code implementations • 16 Jun 2023 • Marcel Hoffmann, Theresa Noegel, Christian Schüßler, Lars Schwenger, Peter Gulden, Dietmar Fey, Martin Vossiek
This paper presents measures to reduce the computation time of automotive synthetic aperture radar (SAR) imaging to achieve real-time capability.
no code implementations • 23 May 2023 • Christian Schüßler, Marcel Hoffmann, Vanessa Wirth, Björn Eskofier, Tim Weyrich, Marc Stamminger, Martin Vossiek
This approach allows not only almost perfect annotations possible, but also allows the annotation of exotic effects, such as multi-path effects or to label signal parts originating from different parts of an object.
1 code implementation • 20 Dec 2021 • Lukas Galke, Iacopo Vagliano, Benedikt Franke, Tobias Zielke, Marcel Hoffmann, Ansgar Scherp
The combination of these two challenges is particularly relevant since newly emerging classes typically resemble only a tiny fraction of the data, adding to the already skewed class distribution.