RadProPoser: Probabilistic Radar Tensor Human Pose Estimation That Knows Its Limits

Müller J, Engel L, Dorschky E, Krauß D, Ullmann I, Vossiek M, Eskofier B (2026)

Publication Type: Conference contribution, Conference Contribution

Publication year: 2026

Event location: Maastricht - Maastrichts Expositie en Congres Centrum (MECC) NL

URI: https://ieeexplore.ieee.org/abstract/document/11729073

DOI: 10.1109/IJCNN69854.2026.11729073

Authors with CRIS profile

Jonas Müller Machine Learning and Data Analytics Lab Lukas Engel Lehrstuhl für Hochfrequenztechnik (LHFT) Eva Dorschky Machine Learning and Data Analytics Lab Daniel Krauß Machine Learning and Data Analytics Lab Ingrid Ullmann Lehrstuhl für Hochfrequenztechnik (LHFT) Martin Vossiek Lehrstuhl für Hochfrequenztechnik (LHFT) Björn Eskofier Department Artificial Intelligence in Biomedical Engineering (AIBE)

How to cite

APA:

Müller, J., Engel, L., Dorschky, E., Krauß, D., Ullmann, I., Vossiek, M., & Eskofier, B. (2026). RadProPoser: Probabilistic Radar Tensor Human Pose Estimation That Knows Its Limits. In Proceedings of the International Joint Conference on Neural Networks (IJCNN). Maastricht - Maastrichts Expositie en Congres Centrum (MECC), NL.

MLA:

Müller, Jonas, et al. "RadProPoser: Probabilistic Radar Tensor Human Pose Estimation That Knows Its Limits." Proceedings of the International Joint Conference on Neural Networks (IJCNN), Maastricht - Maastrichts Expositie en Congres Centrum (MECC) 2026.

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