The performance of detection in COCO
Peipeilvcm opened this issue · comments
Based on MMDetection,train COCO2017 & val COCO2017
FasterR-CNN,r50 From torchvision://resnet50
1x: bbox_mAP: 0.3750
FasterR-CNN,r50 From My Reproduction Model Pretrained on ImageNet
1x: bbox_mAP: 0.3580
FasterR-CNN,r50 From Your Pretrained Mode on ImageNetl
1x: bbox_mAP: 0.3550
Which is not as good as expected? Could you give a help?
Did you use SyncBN for each component during the detector training? If not, you should do so.
Please see this config for reference.
The reason can be found in MoCo paper.
Did you use SyncBN for each component during the detector training? If not, you should do so.
Please see this config for reference.
The reason can be found in MoCo paper.
Thanks for your quick reply, I will try it, and updates the results
Based on MMDetection,train COCO2017 & val COCO2017, No freeze stage,Add SyncBN
FasterR-CNN,r50 From torchvision://resnet50
1x: bbox_mAP: 0.3740
FasterR-CNN,r50 From My Reproduction Model Pretrained on ImageNet
1x: bbox_mAP: 0.3780
FasterR-CNN,r50 From Your Pretrained Mode on ImageNetl
1x: bbox_mAP: 0.3750