Label-Aware Ranked Loss for Robust People Counting Using Automotive In-Cabin Radar. - Lorenzo Servadei; Huawei Sun; Julius Ott; Michael Stephan; Souvik Hazra; Thomas Stadelmayer; Daniela Sanchez Lopera; Robert Wille; Avik Santra (ICASSP, 2022)

Uncertainty-based Meta-Reinforcement Learning for Robust Radar Tracking. - Julius Ott; Lorenzo Servadei; Gianfranco Mauro; Thomas Stadelmayer; Avik Santra; Robert Wille (ICMLA, 2022)

MEET: A Monte Carlo Exploration-Exploitation Trade-Off for Buffer Sampling. - Julius Ott; Lorenzo Servadei; Jose A. Arjona-Medina; Enrico Rinaldi; Gianfranco Mauro; Daniela Sanchez Lopera; Michael Stephan; Thomas Stadelmayer; Avik Santra; Robert Wille (ICASSP, 2023)

Temporal Patience: Efficient Adaptive Deep Learning for Embedded Radar Data Processing. - Max Sponner; Julius Ott; Lorenzo Servadei; Bernd Waschneck; Robert Wille; Akash Kumar 001 (CoRR, 2023)

Few-Shot User-Adaptable Radar-Based Breath Signal Sensing. - Gianfranco Mauro; Maria De Carlos Diez; Julius Ott; Lorenzo Servadei; Manuel P. Cuéllar; Diego P. Morales-Santos (Sensors, 2023)

Context-adaptable radar-based people counting via few-shot learning. - Gianfranco Mauro; Ignacio Martinez-Rodriguez; Julius Ott; Lorenzo Servadei; Robert Wille; Manuel P. Cuéllar; Diego P. Morales-Santos (Appl. Intell., 2023)

CaFNet: A Confidence-Driven Framework for Radar Camera Depth Estimation. - Huawei Sun; Hao Feng; Julius Ott; Lorenzo Servadei; Robert Wille (IROS, 2024)

Enhanced Radar Perception via Multi-Task Learning: Towards Refined Data for Sensor Fusion Applications. - Huawei Sun; Hao Feng; Gianfranco Mauro; Julius Ott; Georg Stettinger; Lorenzo Servadei; Robert Wille (IV, 2024)

LiRCDepth: Lightweight Radar-Camera Depth Estimation via Knowledge Distillation and Uncertainty Guidance. - Huawei Sun; Nastassia Vysotskaya; Tobias Sukianto; Hao Feng; Julius Ott; Xiangyuan Peng; Lorenzo Servadei; Robert Wille (ICASSP, 2025)

GET-UP: GEomeTric-aware Depth Estimation with Radar Points UPsampling. - Huawei Sun; Zixu Wang; Hao Feng; Julius Ott; Lorenzo Servadei; Robert Wille (WACV, 2025)

Exploiting Benford's Law for Weight Regularization of Deep Neural Networks. - Julius Ott; Huawei Sun; Enrico Rinaldi; Gianfranco Mauro; Lorenzo Servadei; Robert Wille (Trans. Mach. Learn. Res., 2025)

TRIDE: A Text-assisted Radar-Image weather-aware fusion network for Depth Estimation. - Huawei Sun; Zixu Wang; Hao Feng; Julius Ott; Lorenzo Servadei; Robert Wille (Trans. Mach. Learn. Res., 2025)