HyperAI

Object Detection On Cppe 5

Métriques

AP50
AP75
APL
APM
APS
box AP

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
AP50
AP75
APL
APM
APS
box AP
Paper TitleRepository
Double Heads87.355.260.841.038.652.0CPPE-5: Medical Personal Protective Equipment Dataset
YOLOv379.435.349.028.423.138.5CPPE-5: Medical Personal Protective Equipment Dataset
Sparse RCNN69.644.654.730.630.044.0CPPE-5: Medical Personal Protective Equipment Dataset
Deformable DETR76.952.853.935.236.448.0CPPE-5: Medical Personal Protective Equipment Dataset
RegNet85.351.860.541.135.751.3CPPE-5: Medical Personal Protective Equipment Dataset
TridentNet85.158.362.641.342.652.9CPPE-5: Medical Personal Protective Equipment Dataset
FCOS79.545.951.739.236.744.4CPPE-5: Medical Personal Protective Equipment Dataset
RepPoints75.940.148.036.727.343.0CPPE-5: Medical Personal Protective Equipment Dataset
VarifocalNet82.656.758.842.139.051.0CPPE-5: Medical Personal Protective Equipment Dataset
Empirical Attention86.554.161.043.438.752.5CPPE-5: Medical Personal Protective Equipment Dataset
Deformable Convolutional Network87.155.961.341.436.351.6CPPE-5: Medical Personal Protective Equipment Dataset
Faster RCNN73.847.852.534.730.044.0CPPE-5: Medical Personal Protective Equipment Dataset
Grid RCNN77.950.654.437.243.447.5CPPE-5: Medical Personal Protective Equipment Dataset
Localization Distillation76.558.859.443.045.850.9CPPE-5: Medical Personal Protective Equipment Dataset
FSAF84.748.256.739.645.349.2CPPE-5: Medical Personal Protective Equipment Dataset
SSD57.024.934.623.132.129.50CPPE-5: Medical Personal Protective Equipment Dataset
0 of 16 row(s) selected.