Object Detection on Cars
92.47Top-1 AccuracyCCSSL
Evaluation results
| Method | Links | |
|---|---|---|
| CCSSLPre-trained=ImageNet, Backbone=ResNet-50 (4x), Evaluation Protocol=fine-tune2025.11 | 92.47 | |
| SimMatchV2Pre-trained=ImageNet, Backbone=ResNet-50 (4x), Evaluation Protocol=fine-tune2025.11 | 91.86 | |
| CLOPPre-trained=ImageNet, Backbone=ResNet-50 (4x), Evaluation Protocol=fine-tune2025.11 | 91.71 | |
| SupConPre-trained=ImageNet, Backbone=ResNet-50 (4x), Evaluation Protocol=fine-tune2025.11 | 91.69 | |
| SimCLRPre-trained=ImageNet, Backbone=ResNet-50 (4x), Evaluation Protocol=fine-tune2025.11 | 91.3 | |
| SimMatchPre-trained=ImageNet, Backbone=ResNet-50 (4x), Evaluation Protocol=fine-tune2025.11 | 91.27 | |
| SsCLPre-trained=ImageNet, Backbone=ResNet-50 (4x), Evaluation Protocol=fine-tune2025.11 | 90.89 | |
| FixMatchPre-trained=ImageNet, Backbone=ResNet-50 (4x), Evaluation Protocol=fine-tune2025.11 | 90.04 |