Scene Reconstruction Using Ubiquitous Wireless Signals via Diffusion Posterior Inference Over physics-Grounded Representations
Read the original on arXiv Machine Learning →The paper presents a method for reconstructing building footprints using only wireless channel measurements. It introduces a two‑stage hierarchical framework: first, a physics‑grounded wireless foundation model converts each channel measurement into a scene representation; second, a diffusion model jointly integrates multiple representations to infer and sample the posterior distribution over building occupancy. Experiments show that this approach can accurately recover building footprints and that both the physics‑grounded representations and joint posterior inference are essential for performance.
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