Data checked 2026-08-10. Data checked within the review cycle.
Review cycles are documented on the Methodology page. Methodology
VisDrone Dataset
Official ConfirmedThe dataset for drone based detection and tracking is released, including both image/video, and annotations.
How is it used?
Start from the recorded entry points below, then validate against the technical checklist.
- Official site https://github.com/VisDrone/VisDrone-Dataset
- Repository https://github.com/VisDrone/VisDrone-Dataset
- Documentation https://github.com/VisDrone/VisDrone-Dataset
Technical checklist
- NEEDS REVIEW License identified No license field in any source response
- OK Maintenance signal Active
- OK Verification status official confirmed
- OK Source evidence attached 1 source record(s)
- NEEDS REVIEW Latest version recorded Not recorded
Official Links
Metadata & Governance
| License | License: Unknown — No license field in any source response. |
|---|---|
| Commercial model | unknown |
| Maintenance status | Active |
| Verification status | official_confirmed — confirmed via the official repository API responses in SourceRefs below. |
| Latest version | Not recorded |
| Latest release | Not recorded |
| Last activity | 2026-08-10 |
| Last checked | 2026-08-10 |
| First seen | Not recorded |
Related Resources & Dependencies
No verified relations have been recorded for this resource yet.
Update Events
No verified update events have been recorded for this resource yet.
Related guides
- Reviewing Aerial AI and Dataset Sources — A provenance-first review flow for aerial datasets and model repositories.
- Building an Aerial Dataset Pipeline — A step-by-step path for assembling an aerial detection dataset pipeline from an indexed dataset and model framework.
- Verifying Whether an AI Model Can Deploy to an Edge Platform — A checklist for checking model export support on a target edge platform without inventing performance claims.
- VisDrone Dataset Engineering & Benchmark Guide — An engineering guide for loading, converting, and benchmarking the VisDrone aerial object detection dataset with YOLO models.