AI RESEARCH
GeRaF: Neural Geometry Reconstruction from Radio Frequency Signals
arXiv CS.CV
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ArXi:2605.29097v1 Announce Type: new GeRaF is the first method to use neural implicit learning for near-range 3D geometry reconstruction from radio frequency (RF) signals. Unlike RGB or LiDAR-based methods, RF sensing can see through occlusion but suffers from low resolution and noise due to its lensless imaging nature. While lenses in RGB imaging constrain sampling to 1D rays, RF signals propagate through the entire space,