DetReIDX (A Stress-Test Dataset for Real-World UAV-Based Person Recognition)

We are proud to introduce DetReIDX - is a new benchmark dataset built for real-world, long-range human recognition. It supports key computer vision tasks like person detection, re-identification (ReID), multi-view tracking, and action recognition — all captured in complex outdoor scenes using drones and ground cameras.

The dataset starts with an indoor session where each person is photographed from three angles — left, front, and right — and recorded while walking, enabling motion-based recognition like gait analysis.

In the outdoor sessions, drones capture videos from 18 viewpoints per subject, across different heights (up to 120m), distances, and camera angles (30°, 60°, 90°). Each person wears different outfits across sessions to simulate real-world variation.

Every frame is labeled with bounding boxes and 16 soft biometric attributes (like age, gender, clothing, action), offering fine-grained details for deep analysis.

With over 13+ million annotations and rich visual diversity, DetReIDX sets a new standard for evaluating human-centric AI in aerial and surveillance scenarios.