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Object Detection on MS-COCO 2017 (val) (Accuracy and Efficiency)

55.6Box APYOLOv9
34.90440.27745.6551.023Dec 4, 2018Feb 12, 2020Apr 22, 2021Jul 1, 2022Sep 9, 2023Nov 17, 2024Jan 26, 2026

Evaluation results

MethodLinks
YOLOv9Model Scale=X, Input size=6402026.0155.6——16.77
YOLO-DSModel Scale=X, Input size=6402026.0155——14.99
YOLO11Model Scale=X, Input size=6402026.0154.7——11.3
YOLOv10Model Scale=X, Input size=6402026.0154.4——12.2
YOLO-DSModel Scale=L, Input size=6402026.0154.1——9.31
YOLOv8Model Scale=X, Input size=6402026.0153.9——14.37
YOLO11Model Scale=L, Input size=6402026.0153.4——6.2
YOLOv10Model Scale=L, Input size=6402026.0153.2——8.33
YOLOv9Model Scale=L, Input size=6402026.0153——7.16
YOLOv8Model Scale=L, Input size=6402026.0152.9——9.06
YOLO-DSModel Scale=M, Input size=6402026.0151.6——6.09
YOLO11Model Scale=M, Input size=6402026.0151.5——4.7
YOLOv9Model Scale=M, Input size=6402026.0151.4——6.43
YOLOv10Model Scale=M, Input size=6402026.0151.1——5.48
YOLOv8Model Scale=M, Input size=6402026.0150.2——5.86
YOLO11Model Scale=S, Input size=6402026.0147——2.5
YOLOv9Model Scale=S, Input size=6402026.0146.8——3.54
YOLO-DSModel Scale=S, Input size=6402026.0146.6——2.77
YOLOv10Model Scale=S, Input size=6402026.0146.3——2.66
Efficient AttentionBackbone=ResNeXt-1012018.1244.92.95.3—
YOLOv8Model Scale=S, Input size=6402026.0144.9——2.66
LatentGNNBackbone=ResNeXt-1012018.1243.211.17.6—
Efficient AttentionBackbone=ResNet-1012018.1243.12.95.3—
Efficient AttentionBackbone=ResNet-502018.1241.22.95.3—
LatentGNNBackbone=ResNet-1012018.124111.17.6—
LatentGNNBackbone=ResNet-502018.1239.511.17.6—
YOLO11Model Scale=N, Input size=6402026.0139.5——1.5
YOLO-DSModel Scale=N, Input size=6402026.0138.7——1.51
YOLOv10Model Scale=N, Input size=6402026.0138.5——1.56
YOLOv9Model Scale=N, Input size=6402026.0138.3——2.3
YOLOv8Model Scale=N, Input size=6402026.0137.3——1.47
CGNLBackbone=ResNet-502018.1235.721.75.7—