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Object Detection On Cppe 5

Metrics

AP50

AP75

APL

APM

APS

box AP

Results

Performance results of various models on this benchmark

							Paper Title	Repository
Double Heads	87.3	55.2	60.8	41.0	38.6	52.0	CPPE-5: Medical Personal Protective Equipment Dataset
Deformable Convolutional Network	87.1	55.9	61.3	41.4	36.3	51.6	CPPE-5: Medical Personal Protective Equipment Dataset
Empirical Attention	86.5	54.1	61.0	43.4	38.7	52.5	CPPE-5: Medical Personal Protective Equipment Dataset
RegNet	85.3	51.8	60.5	41.1	35.7	51.3	CPPE-5: Medical Personal Protective Equipment Dataset
TridentNet	85.1	58.3	62.6	41.3	42.6	52.9	CPPE-5: Medical Personal Protective Equipment Dataset
FSAF	84.7	48.2	56.7	39.6	45.3	49.2	CPPE-5: Medical Personal Protective Equipment Dataset
VarifocalNet	82.6	56.7	58.8	42.1	39.0	51.0	CPPE-5: Medical Personal Protective Equipment Dataset
FCOS	79.5	45.9	51.7	39.2	36.7	44.4	CPPE-5: Medical Personal Protective Equipment Dataset
YOLOv3	79.4	35.3	49.0	28.4	23.1	38.5	CPPE-5: Medical Personal Protective Equipment Dataset
Grid RCNN	77.9	50.6	54.4	37.2	43.4	47.5	CPPE-5: Medical Personal Protective Equipment Dataset
Deformable DETR	76.9	52.8	53.9	35.2	36.4	48.0	CPPE-5: Medical Personal Protective Equipment Dataset
Localization Distillation	76.5	58.8	59.4	43.0	45.8	50.9	CPPE-5: Medical Personal Protective Equipment Dataset
RepPoints	75.9	40.1	48.0	36.7	27.3	43.0	CPPE-5: Medical Personal Protective Equipment Dataset
Faster RCNN	73.8	47.8	52.5	34.7	30.0	44.0	CPPE-5: Medical Personal Protective Equipment Dataset
Sparse RCNN	69.6	44.6	54.7	30.6	30.0	44.0	CPPE-5: Medical Personal Protective Equipment Dataset
SSD	57.0	24.9	34.6	23.1	32.1	29.50	CPPE-5: Medical Personal Protective Equipment Dataset

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Object Detection On Cppe 5 | SOTA | HyperAI