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.
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A DFrFT-based algorithm detects and removes interference chirps in FMCW radar signals via compression and zeroing, with reduced-complexity handling for multiple interferers, outperforming references on synthetic data.
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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.
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FMCW Radar Interference Mitigation based on the Fractional Fourier Transform
A DFrFT-based algorithm detects and removes interference chirps in FMCW radar signals via compression and zeroing, with reduced-complexity handling for multiple interferers, outperforming references on synthetic data.