DoRF++ recovers a latent 3D velocity sequence from CSI Doppler projections via rank-3 matrix factorization, re-projects it onto a sphere, and classifies gestures with spherical attention, reporting 80.4% cross-user accuracy on a four-gesture Wi-Fi dataset.
A survey on behavior recognition using Wi-Fi channel state information,
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DoRF++: Spherical Representation Learning over Doppler Radiance Fields for Robust Wi-Fi Sensing
DoRF++ recovers a latent 3D velocity sequence from CSI Doppler projections via rank-3 matrix factorization, re-projects it onto a sphere, and classifies gestures with spherical attention, reporting 80.4% cross-user accuracy on a four-gesture Wi-Fi dataset.