29 lines
1.7 KiB
Markdown
29 lines
1.7 KiB
Markdown
# RetinaNet (Focal Loss for Dense Object Detection)
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## Model Zoo
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| Backbone | Model | imgs/GPU | lr schedule | FPS | Box AP | download | config |
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| ------------ | --------- | -------- | ----------- | --- | ------ | ---------- | ----------- |
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| ResNet50-FPN | RetinaNet | 2 | 1x | --- | 37.5 | [model](https://bj.bcebos.com/v1/paddledet/models/retinanet_r50_fpn_1x_coco.pdparams) | [config](./retinanet_r50_fpn_1x_coco.yml) |
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| ResNet50-FPN | RetinaNet | 2 | 2x | --- | 39.1 | [model](https://bj.bcebos.com/v1/paddledet/models/retinanet_r50_fpn_2x_coco.pdparams) | [config](./retinanet_r50_fpn_2x_coco.yml) |
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| ResNet101-FPN| RetinaNet | 2 | 2x | --- | 40.6 | [model](https://paddledet.bj.bcebos.com/models/retinanet_r101_fpn_2x_coco.pdparams) | [config](./retinanet_r101_fpn_2x_coco.yml) |
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| ResNet50-FPN | RetinaNet + [FGD](../slim/distill/README.md) | 2 | 2x | --- | 40.8 | [model](https://bj.bcebos.com/v1/paddledet/models/retinanet_r101_distill_r50_2x_coco.pdparams) | [config](./retinanet_r50_fpn_2x_coco.yml)/[slim_config](../slim/distill/retinanet_resnet101_coco_distill.yml) |
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**Notes:**
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- The ResNet50-FPN are trained on COCO train2017 with 8 GPUs. Both ResNet101-FPN and ResNet50-FPN with [FGD](../slim/distill/README.md) are trained on COCO train2017 with 4 GPUs.
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- All above models are evaluated on val2017. Box AP=`mAP(IoU=0.5:0.95)`.
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## Citation
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```latex
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@inproceedings{lin2017focal,
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title={Focal loss for dense object detection},
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author={Lin, Tsung-Yi and Goyal, Priya and Girshick, Ross and He, Kaiming and Doll{\'a}r, Piotr},
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booktitle={Proceedings of the IEEE international conference on computer vision},
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year={2017}
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}
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```
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