Object Detection on Casting Billet
79.8mAP@.5AGBP
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| AGBPBackbone=Swin-Base, Pretraining Dataset=Industrial, Base Pretraining=SimMIM2025.09 | 79.8 | 44.3 | |
| AGSSPBackbone=Swin-Base, Pretraining Dataset=Industrial, Base Pretraining=SimMIM2025.09 | 78.8 | 48.4 | |
| SimMIMBackbone=Swin-Base, Pretraining Dataset=ImageNet2025.09 | 78.3 | 44.3 | |
| AGSSPBackbone=Swin-Base, Pretraining Dataset=Industrial, Base Pretraining=Classification2025.09 | 77.7 | 45 | |
| AGSSPBackbone=CSPDarknet, Pretraining Dataset=Industrial, Base Pretraining=Classification2025.09 | 77.2 | 44.9 | |
| AGBPBackbone=Swin-Base, Pretraining Dataset=Industrial, Base Pretraining=Classification2025.09 | 76.8 | 39 | |
| SimMIMBackbone=Swin-Base, Pretraining Dataset=Industrial2025.09 | 76.5 | 41.5 | |
| ClassificationBackbone=Swin-Base, Pretraining Dataset=ImageNet2025.09 | 75.7 | 37.7 | |
| DetectionBackbone=CSPDarknet, Pretraining Dataset=COCO2025.09 | 75.1 | 43.9 | |
| AGBPBackbone=CSPDarknet, Pretraining Dataset=Industrial, Base Pretraining=Classification2025.09 | 74.9 | 37.5 | |
| AGSSPBackbone=ResNet50, Pretraining Dataset=Industrial, Base Pretraining=Classification2025.09 | 74.5 | 42.5 | |
| Training from scratchBackbone=CSPDarknet2025.09 | 74.2 | 37.1 | |
| AGSSPBackbone=WideResNet50, Pretraining Dataset=Industrial, Base Pretraining=Classification2025.09 | 73.5 | 42.5 | |
| ClassificationBackbone=Swin-Base, Pretraining Dataset=Industrial2025.09 | 73.3 | 36 | |
| ClassificationBackbone=CSPDarknet, Pretraining Dataset=Industrial2025.09 | 72.8 | 34.7 | |
| AGBPBackbone=WideResNet50, Pretraining Dataset=Industrial, Base Pretraining=Classification2025.09 | 72.5 | 37.8 | |
| AGBPBackbone=ResNet50, Pretraining Dataset=Industrial, Base Pretraining=Classification2025.09 | 72 | 36.1 | |
| ClassificationBackbone=CSPDarknet, Pretraining Dataset=ImageNet2025.09 | 71.6 | 33.5 | |
| ClassificationBackbone=WideResNet50, Pretraining Dataset=ImageNet2025.09 | 71.5 | 34.6 | |
| AGBPBackbone=ResNet50, Pretraining Dataset=Industrial, Base Pretraining=MoCov32025.09 | 71.4 | 33.1 | |
| MoCov3Backbone=ResNet50, Pretraining Dataset=Industrial2025.09 | 71.3 | 36.8 | |
| MoCov3Backbone=ResNet50, Pretraining Dataset=ImageNet2025.09 | 70.2 | 33.9 | |
| ClassificationBackbone=ResNet50, Pretraining Dataset=ImageNet2025.09 | 69.1 | 32.3 | |
| ClassificationBackbone=ResNet50, Pretraining Dataset=Industrial2025.09 | 69.1 | 33.6 | |
| DINOv1Backbone=ResNet50, Pretraining Dataset=ImageNet2025.09 | 67.8 | 34.5 | |
| Training from scratchBackbone=Swin-Base2025.09 | 61.1 | 30.1 | |
| Training from scratchBackbone=ResNet502025.09 | 56.7 | 27 |