Object Detection on FDD-48 (test)
42.2mAP50:95FDDet
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| FDDetBackbone=RTMDet-x, Param.(M)=94.8, Pre-trained Data=COCO2026.05 | 42.2 | 49 | 46 | |
| EfficientDetBackbone=EfficientNet-b3, Param.(M)=12.0, Pre-trained Data=COCO2026.05 | 41.7 | 46.9 | 45 | |
| VitDetBackbone=ViT-B, Param.(M)=108.1, Pre-trained Data=COCO2026.05 | 41.5 | 47 | 44.4 | |
| YOLOv10Backbone=YOLOv10-x, Param.(M)=29.5, Pre-trained Data=COCO2026.05 | 41.2 | 46.3 | 45 | |
| RTMDetBackbone=RTMDet-x, Param.(M)=94.8, Pre-trained Data=COCO2026.05 | 40 | 45.6 | 43.7 | |
| CO-DETRBackbone=Swin-L, Param.(M)=235.2, Pre-trained Data=Objects365, COCO2026.05 | 40 | 43.7 | 42.8 | |
| YOLOXBackbone=YOLOX-x, Param.(M)=99.0, Pre-trained Data=COCO2026.05 | 38.9 | 44.3 | 42.7 | |
| DINOBackbone=R-50, Param.(M)=47.6, Pre-trained Data=COCO2026.05 | 38.2 | 42.8 | 41 | |
| DDQBackbone=R-50, Param.(M)=48.5, Pre-trained Data=COCO2026.05 | 37.6 | 41.6 | 40.4 | |
| DAB-DETRBackbone=R-50, Param.(M)=43.7, Pre-trained Data=COCO2026.05 | 34.7 | 40.2 | 38.3 | |
| GLIPBackbone=Swin-T, Param.(M)=231.8, Pre-trained Data=O365, GoldG, CC3M, SBU2026.05 | 25 | 27.7 | 26.6 |