Datasets:
GRaF-sim — Simulated RF Spectrum Dataset
Simulated wireless channel spectra for 18 indoor scenes, released with the CVPR 2026 paper "Generalizable Radio-Frequency Radiance Fields for Spatial Spectrum Synthesis" by Kang Yang, Yuning Chen, and Wan Du.
📄 Paper: arXiv:2502.05708 · 💻 Code: github.com/kangyang73/GRaF · 🤖 Models: kyang73/GRaF-pretrained
Used to train and evaluate GRaF, a generalizable radio field model.
Each scene is modeled as a box room with ITU-material walls and furniture primitives. For every transmitter position, Sionna ray-tracing computes the channel response at an 8 × 8 receiver array, and conventional beamforming over a 360° × 90° azimuth–elevation grid produces the final spatial spectrum image.
Scenes
Each category contains six scene variants with increasing furniture/clutter.
| Category | Room | Room size (m) | Scenes |
|---|---|---|---|
| A | Conference Room | 8.0 × 6.0 × 3.0 | D2–D7 |
| B | Classroom | 10.0 × 7.0 × 3.0 | D8–D13 |
| C | Bedroom | 5.0 × 4.0 × 2.8 | D14–D19 |
Per-scene layout
D<i>/
├── gateway_info.yml # room size + receiver (gateway) pose
├── tx_pos.csv # 5 340 transmitter positions (x, y, z)
└── spectrum/
├── 00001.png # 360 × 90 grayscale spectrum (azimuth × elevation)
├── 00002.png
└── ... # one image per TX position
Totals: 18 scenes × 5 340 samples ≈ 96 K spectrum images, ~785 MB.
Download
from huggingface_hub import snapshot_download
snapshot_download("kyang73/GRaF-sim", repo_type="dataset", local_dir="data")
Or via CLI:
hf download kyang73/GRaF-sim --repo-type dataset --local-dir data
Citation
If you use this dataset, please cite:
@inproceedings{Yang2026_GRaF,
author = {Kang Yang and Yuning Chen and Wan Du},
title = {Generalizable Radio-Frequency Radiance Fields for Spatial Spectrum Synthesis},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2026},
}
License
Released under the BSD 3-Clause License. Copyright (c) 2025, Kang Yang, Yuning Chen, and Wan Du. See the GRaF repository for full terms.
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