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cs.CV2026
Beam-Wise Statistical Background Subtraction for Static Roadside LiDAR: A Cross-Sensor Benchmark Study
Alexander Baumann, Marcel Vosshans, Thao Dang
Background subtraction is a key preprocessing step for infrastructure-based LiDAR perception, enabling efficient isolation of dynamic traffic participants without semantic annotati…
cs.CV2026
Image-based Quantification of Postural Deviations on Patients with Cervical Dystonia: A Machine Learning Approach Using Synthetic Training Data
Roland Stenger, Sebastian Löns, Nele Brügge +36
Cervical dystonia (CD) is the most common form of dystonia, yet current assessment relies on subjective clinical rating scales, such as the Toronto Western Spasmodic Torticollis Ra…
cs.CV2026
CARL: Camera-Agnostic Representation Learning for Spectral Image Analysis
Alexander Baumann, Leonardo Ayala, Silvia Seidlitz +5
Spectral imaging offers promising applications across diverse domains, including medicine and urban scene understanding, and is already established as a critical modality in remote…