Object Detection on GC10-Det
67.7mAP@.5AGSSP
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| AGSSPBackbone=Swin-Base, Pretraining Dataset=Industrial, Base Pretraining=SimMIM2025.09 | 67.7 | 34 | |
| AGSSPBackbone=CSPDarknet, Pretraining Dataset=Industrial, Base Pretraining=Classification2025.09 | 66.6 | 32.3 | |
| AGSSPBackbone=ResNet50, Pretraining Dataset=Industrial, Base Pretraining=Classification2025.09 | 65.3 | 31.5 | |
| DetectionBackbone=CSPDarknet, Pretraining Dataset=COCO2025.09 | 63.8 | 31.5 | |
| AGSSPBackbone=WideResNet50, Pretraining Dataset=Industrial, Base Pretraining=Classification2025.09 | 63.7 | 32.5 | |
| AGSSPBackbone=Swin-Base, Pretraining Dataset=Industrial, Base Pretraining=Classification2025.09 | 63.5 | 32 | |
| SimMIMBackbone=Swin-Base, Pretraining Dataset=ImageNet2025.09 | 63.4 | 31 | |
| ClassificationBackbone=Swin-Base, Pretraining Dataset=ImageNet2025.09 | 63.1 | 31.8 | |
| AGBPBackbone=ResNet50, Pretraining Dataset=Industrial, Base Pretraining=Classification2025.09 | 62.8 | 29 | |
| ClassificationBackbone=CSPDarknet, Pretraining Dataset=ImageNet2025.09 | 62.6 | 29.4 | |
| ClassificationBackbone=CSPDarknet, Pretraining Dataset=Industrial2025.09 | 62.3 | 29.1 | |
| AGBPBackbone=CSPDarknet, Pretraining Dataset=Industrial, Base Pretraining=Classification2025.09 | 62.1 | 29.5 | |
| AGBPBackbone=Swin-Base, Pretraining Dataset=Industrial, Base Pretraining=SimMIM2025.09 | 62.1 | 31.4 | |
| AGBPBackbone=WideResNet50, Pretraining Dataset=Industrial, Base Pretraining=Classification2025.09 | 62 | 29.8 | |
| ClassificationBackbone=WideResNet50, Pretraining Dataset=ImageNet2025.09 | 61.8 | 29.9 | |
| Training from scratchBackbone=CSPDarknet2025.09 | 61.6 | 30 | |
| ClassificationBackbone=ResNet50, Pretraining Dataset=ImageNet2025.09 | 61.4 | 29.5 | |
| MoCov3Backbone=ResNet50, Pretraining Dataset=Industrial2025.09 | 61.2 | 27.2 | |
| AGBPBackbone=Swin-Base, Pretraining Dataset=Industrial, Base Pretraining=Classification2025.09 | 61.2 | 30.3 | |
| SimMIMBackbone=Swin-Base, Pretraining Dataset=Industrial2025.09 | 60.9 | 29.7 | |
| DINOv1Backbone=ResNet50, Pretraining Dataset=ImageNet2025.09 | 60.2 | 27.7 | |
| ClassificationBackbone=ResNet50, Pretraining Dataset=Industrial2025.09 | 60.1 | 29.1 | |
| ClassificationBackbone=Swin-Base, Pretraining Dataset=Industrial2025.09 | 60 | 28.2 | |
| MoCov3Backbone=ResNet50, Pretraining Dataset=ImageNet2025.09 | 59.9 | 28.4 | |
| AGBPBackbone=ResNet50, Pretraining Dataset=Industrial, Base Pretraining=MoCov32025.09 | 58.6 | 27.7 | |
| Training from scratchBackbone=Swin-Base2025.09 | 54.8 | 26.5 | |
| Training from scratchBackbone=ResNet502025.09 | 54.1 | 25.8 |