Table 3 Comparison of YOLOV8n and YOLO-GL on the VisDrone dataset.
From: YOLO-GL for efficient multi-target detection in large FOV via hierarchical feature fusion
Class | YOLOV8n | YOLO-GL | ||||||
|---|---|---|---|---|---|---|---|---|
P | R | mAP@0.5 | mAP@0.5:0.95 | P | R | mAP@0.5 | mAP@0.5:0.95 | |
All | 47.2 | 34.6 | 35.2 | 20.6 | 47.9 | 34.4 | 35.6 | 20.9 |
Pedestrian | 47.4 | 36.6 | 37.8 | 16.5 | 44.4 | 37.8 | 37.8 | 16.5 |
People | 51.3 | 25.1 | 29.3 | 10.7 | 56.6 | 23.0 | 30.0 | 11.1 |
Bicycle | 29.6 | 9.63 | 9.54 | 3.94 | 29.7 | 9.87 | 9.92 | 4.05 |
Car | 64.7 | 76.8 | 77.2 | 53.6 | 65.9 | 76.6 | 77.5 | 54.0 |
Van | 52.2 | 38.5 | 40.8 | 28.2 | 52.0 | 40.6 | 41.3 | 28.9 |
Truck | 47.3 | 30.9 | 30.9 | 19.7 | 48.5 | 30.8 | 31.6 | 20.2 |
Tricycle | 38.0 | 27.0 | 23.5 | 12.9 | 38.8 | 27.0 | 24.2 | 13.5 |
Awning-tricycle | 29.8 | 15.5 | 13.0 | 8.22 | 26.4 | 18.0 | 14.3 | 8.96 |
Bus | 60.9 | 46.2 | 50.7 | 35.2 | 63.1 | 43.4 | 49.3 | 35.1 |
Motor | 50.5 | 39.4 | 39.2 | 16.7 | 53.5 | 37.1 | 40.1 | 17.0 |
