collaborators

15 papers

cs.CV2026

You Only Flow Once: Calibrated and Real-Time Radar Pose Estimation with Multi-Hypothesis Normalizing Flows

Jonas Leo Mueller, Sebastian Hoefler, Dario Zanca +3

Sparse and noisy millimeter-wave radar point cloud observations often correspond to multiple plausible human poses, making deterministic pose estimation fundamentally ill-posed. Ye…

cs.CV2026

Learning Biomechanically Plausible Human Motion from Sparse Radar Point Clouds

Jonas Leo Mueller, Markus Gambietz, Alexander Weiss +2

Radar-based human pose estimation has focused on improving learning algorithms while representing the body as unconstrained keypoint coordinates. We address the underexplored dimen…

eess.SP2026

Multi-Channel Soil Moisture Measurement: High Accuracy and Low Crosstalk Through Optical-Semiconductor Based Differential Sensing

Thomas Maier, Charlotte Rohleder, Lukas Kamm +3

Soil moisture measurement plays a key role in irrigation and environmental management. Yet it remains unreliable due to heterogeneous soils, limited sensing volumes, temperature dr…

cs.LG2026

Robust and Efficient Writer-Independent IMU-Based Handwriting Recognition

Jindong Li, Tim Hamann, Jens Barth +3

Handwriting recognition (HWR) using inertial measurement unit (IMU) data remains challenging due to variations in writing styles and the limited availability of datasets. Previous…

cs.CL2026

How Human-Like Are Large Language Models? A Register-Aware Linguistic Evaluation Framework

Björn Nieth, Marianna Gracheva, Michaela Mahlberg +2

While factual correctness and task-performance have been in focus of Large Language Model (LLM) research for a long time, the fundamental question of how human-like generated texts…

cs.CV2026

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

Jonas Leo Mueller, Lukas Engel, Eva Dorschky +4

Radar-based human pose estimation enables privacy-preserving motion tracking for ambient intelligence, yet the noisy nature of radar sensing makes uncertainty quantification essent…