AI RESEARCH
RadProPoser: Probabilistic Radar Tensor Human Pose Estimation That Knows Its Limits
arXiv CS.CV
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ArXi:2508.03578v2 Announce Type: replace Radar-based human pose estimation enables privacy-preserving motion tracking for ambient intelligence, yet the noisy nature of radar sensing makes uncertainty quantification essential. We present RadProPoser, an end-to-end probabilistic framework that predicts three-dimensional body joints with per-joint uncertainties from raw radar tensor data.