RadProPoser uses a variational encoder-decoder with spectral attention to predict 3D poses and aleatoric uncertainties from radar tensors, achieving 6.425 cm MPJPE on a new benchmark and 5.042 cm on HuPR with calibrated uncertainties.
Normalizing flow ensembles for rich aleatoric and epistemic uncertainty modeling
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RadProPoser: Probabilistic Radar Tensor Human Pose Estimation That Knows Its Limits
RadProPoser uses a variational encoder-decoder with spectral attention to predict 3D poses and aleatoric uncertainties from radar tensors, achieving 6.425 cm MPJPE on a new benchmark and 5.042 cm on HuPR with calibrated uncertainties.