Scale your C-UAS data collection to petascale with no labeling.
UAV Multimodal Data
The foundational dataset for C-UAS sensing. UAV Multimodal Data delivers densely annotated samples of UAV targets across every operational scenario — from Group 1 micro-drones against cluttered urban backgrounds to fixed-wing platforms at range against open sky.
80+ C-UAS-relevant object classes. Pixel-level instance segmentation. Oriented bounding boxes. Multi-spectral coverage across RGB, LWIR, and MWIR — because real-world counter-drone operations don't happen in a single spectrum.
Every annotation ships with positioning accurate to 1 cm, coordinated timestamps across all trajectories, and full camera calibration intrinsics — tunable to match your platform. No guesswork. Plug it straight into your pipeline.
Built for teams shipping C-UAS systems, not publishing papers.
4096 × 3072 · RGB · GSD 0.3m
UAV Benchmark
| System | Detection mAP | Tracking MOTA | Classification F1 | Latency P95 | Status |
|---|---|---|---|---|---|
| System A | 91.2% | 82.1% | 0.89 | 87ms | Certified |
| System B | 86.4% | 76.3% | 0.84 | 112ms | Certified |
| System C | 78.9% | 68.7% | 0.79 | 156ms | Certified |
| System D | 72.1% | 61.2% | 0.71 | 203ms | Not Certified |
| Your System | — | — | — | — | ? |
UAV Sensing Model
C-UAS Detection Performance
Off-the-shelf C-UAS sensing. UAV Sensing Model ships pre-trained on UAV Multimodal Data — delivering state-of-the-art drone detection, tracking, and instance segmentation across visible and infrared. No training pipeline. No ML team. Deploy to your counter-drone system this week.
Optimized for real-time inference on NVIDIA Jetson, GPU servers, and ONNX-compatible runtimes. Handles fixed-wing UAS, rotary-wing UAS, and Group 1–3 platforms across cluttered backgrounds, adverse weather, and low-contrast thermal scenes.
Trained on C-UAS data. Validated on C-UAS scenarios. Deployed by C-UAS operators.