{"repo":"yeehengwang/RadCloudSplat","free":true,"listed":false,"github":"https://github.com/yeehengwang/RadCloudSplat","clone":"git clone https://github.com/yeehengwang/RadCloudSplat.git","description":"Official implementation of “RadCloudSplat: Scatterer-Driven 3D Gaussian Splatting with Point-Cloud Priors for Radiomap Extrapolation,” IEEE INFOCOM 2026. Camera-free radio-frequency Gaussian splatting for radiomap and RSS extrapolation with LiDAR point-cloud priors.","language":"Python","stars":20,"topics":["3d-gaussian-splatting","gaussian-splatting","lidar","lidar-point-cloud","multi-path-propagation","official-implementation","point-cloud","radio-frequency","radio-map","radiomap"],"license":"MIT","category":"productivity","readme_excerpt":"RadCloudSplat Official implementation of: RadCloudSplat: Scatterer-Driven 3D Gaussian Splatting with Point-Cloud Priors for Radiomap Extrapolation Yiheng Wang, Ye Xue, Shutao Zhang, Hongmiao Fan and Tsung-Hui Chang Thanks for your interest in our work. This repository contains code and links to the RadCloudSplat method for radiomap extrapolation, which has been accepted by IEEE INFOCOM 2026 . More information can be refered to: - Paper: arXiv - Published version: IEEE Xplore - Code: This repository - Project page: Project Page - License: MIT Introduction In this work, we first extended 3DGS to the radio frequency domain, leveraging camera-free RadCloudSplat to extrapolate RSSs with high accuracy from sparse measurements in an outdoor environment. By efficiently selecting the means of key virtual scatterers from dense point clouds aided by the relaxed-mean (RM) scheme , the model captured intricate multi-path propagation characteristics . Experiments and analysis validated the effectiveness of these scatterers, advancing the state-of-the-art in wireless network modeling and extrapolation performance and highlighting the transformative potential of integrating advanced 3D modeling techniques with wireless propagation analysis for next-generation applications in the radio domain. Schematic illustration of RadCloudSplat , comprising three major parts: 1) Relaxed-Mean Reparameterization for Key Virtual Scatters Positions Extraction. 2) Camera-Free RadCloudSplat Model for RSS Synth","default_branch":null,"files":null,"tree":[],"storefront":"/r/yeehengwang","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/yeehengwang/RadCloudSplat/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}