We present a practical system that reconstructs both line-of-sight (LOS) and non-line-of-sight (NLOS) 3D scenes using a single mmWave radar.

This paper introduces and evaluates G2Sphere, a general method for mapping object geometries to spherical signals using equivariant neural networks and the Fourier Transform.

GeRaF is the first method to use neural implicit learning for near-range 3D geometry reconstruction from radio frequency (RF) signals.