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RetinaNet (Focal Loss for Dense Object Detection)

Model Zoo

Backbone Model imgs/GPU lr schedule FPS Box AP download config
ResNet50-FPN RetinaNet 2 1x --- 37.5 model config
ResNet50-FPN RetinaNet 2 2x --- 39.1 model config
ResNet101-FPN RetinaNet 2 2x --- 40.6 model config
ResNet50-FPN RetinaNet + FGD 2 2x --- 40.8 model config/slim_config

Notes:

  • The ResNet50-FPN are trained on COCO train2017 with 8 GPUs. Both ResNet101-FPN and ResNet50-FPN with FGD are trained on COCO train2017 with 4 GPUs.
  • All above models are evaluated on val2017. Box AP=mAP(IoU=0.5:0.95).

Citation

@inproceedings{lin2017focal,
  title={Focal loss for dense object detection},
  author={Lin, Tsung-Yi and Goyal, Priya and Girshick, Ross and He, Kaiming and Doll{\'a}r, Piotr},
  booktitle={Proceedings of the IEEE international conference on computer vision},
  year={2017}
}