RadTwin conditions a neural radio-propagation model on scene point clouds via physics-informed sparse attention, achieving 0.846 SSIM and 0.023 LPIPS on dynamic indoor scenes without retraining.
Newrf: A deep learning framework for wireless radiation field reconstruction and channel prediction
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2026 3verdicts
UNVERDICTED 3representative citing papers
RFIR framework embeds RF-aware BSDF into Gaussian splatting for decoupled RF scene modeling, generalizing RCS synthesis, RSSI prediction, and wireless scene editability with performance gains.
RF-CMG synthesizes high-quality mmWave and RFID signals from WiFi using a diffusion model with Modality-Guided Embedding for high-frequency details and Low-Frequency Modality Consistency to preserve physical structure.
citing papers explorer
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RadTwin: Generalizable Wireless Digital Twin for Dynamic Environments
RadTwin conditions a neural radio-propagation model on scene point clouds via physics-informed sparse attention, achieving 0.846 SSIM and 0.023 LPIPS on dynamic indoor scenes without retraining.
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Radio-Frequency Inverse Rendering for Wireless Environment Modeling
RFIR framework embeds RF-aware BSDF into Gaussian splatting for decoupled RF scene modeling, generalizing RCS synthesis, RSSI prediction, and wireless scene editability with performance gains.
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Cross-Modal Generation: From Commodity WiFi to High-Fidelity mmWave and RFID Sensing
RF-CMG synthesizes high-quality mmWave and RFID signals from WiFi using a diffusion model with Modality-Guided Embedding for high-frequency details and Low-Frequency Modality Consistency to preserve physical structure.