32 lines
1.9 KiB
Markdown
32 lines
1.9 KiB
Markdown
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# FCOS for Object Detection
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## Introduction
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FCOS (Fully Convolutional One-Stage Object Detection) is a fast anchor-free object detection framework with strong performance. We reproduced the model of the paper, and improved and optimized the accuracy of the FCOS.
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**Highlights:**
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- Training Time: The training time of the model of `fcos_r50_fpn_1x` on Tesla v100 with 8 GPU is only 8.5 hours.
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## Model Zoo
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| Backbone | Model | images/GPU | lr schedule |FPS | Box AP | download | config |
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| :-------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: |
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| ResNet50-FPN | FCOS | 2 | 1x | ---- | 39.6 | [download](https://paddledet.bj.bcebos.com/models/fcos_r50_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.0/configs/fcos/fcos_r50_fpn_1x_coco.yml) |
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| ResNet50-FPN | FCOS+DCN | 2 | 1x | ---- | 44.3 | [download](https://paddledet.bj.bcebos.com/models/fcos_dcn_r50_fpn_1x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.0/configs/fcos/fcos_dcn_r50_fpn_1x_coco.yml) |
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| ResNet50-FPN | FCOS+multiscale_train | 2 | 2x | ---- | 41.8 | [download](https://paddledet.bj.bcebos.com/models/fcos_r50_fpn_multiscale_2x_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.0/configs/fcos/fcos_r50_fpn_multiscale_2x_coco.yml) |
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**Notes:**
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- FCOS is trained on COCO train2017 dataset and evaluated on val2017 results of `mAP(IoU=0.5:0.95)`.
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## Citations
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```
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@inproceedings{tian2019fcos,
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title = {{FCOS}: Fully Convolutional One-Stage Object Detection},
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author = {Tian, Zhi and Shen, Chunhua and Chen, Hao and He, Tong},
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booktitle = {Proc. Int. Conf. Computer Vision (ICCV)},
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year = {2019}
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}
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```
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