URF-GS creates a single radiation field from visual and wireless observations via 3D Gaussian splatting to predict radio signals at any location and configuration with higher accuracy and fewer samples than prior NeRF approaches.
arXiv preprint arXiv:2507.04595 (2025) 22
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 3verdicts
UNVERDICTED 3roles
background 1polarities
background 1representative citing papers
TeRFS models dynamic radio fields via anisotropic spherical Gaussians bound to analytical temporal envelopes that enable explicit multipath birth-and-death, delivering 11.5% lower MSE and 6.9x faster training than baselines.
PointNeRT is a neural surrogate for ray tracing that ingests point clouds and sequentially predicts multipath propagation and attenuation under physics constraints.
citing papers explorer
-
Bridging Visual and Wireless Sensing via a Unified Radiation Field for 3D Radio Map Construction
URF-GS creates a single radiation field from visual and wireless observations via 3D Gaussian splatting to predict radio signals at any location and configuration with higher accuracy and fewer samples than prior NeRF approaches.
-
TeRFS: Temporal-Evolving Radio Field Synthesis
TeRFS models dynamic radio fields via anisotropic spherical Gaussians bound to analytical temporal envelopes that enable explicit multipath birth-and-death, delivering 11.5% lower MSE and 6.9x faster training than baselines.
-
PointNeRT: A Physics Aware Neural Ray Tracing Surrogate for Propagation Channel Modeling
PointNeRT is a neural surrogate for ray tracing that ingests point clouds and sequentially predicts multipath propagation and attenuation under physics constraints.