# FCOS for Object Detection ## Introduction 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. **Highlights:** - Training Time: The training time of the model of `fcos_r50_fpn_1x` on Tesla v100 with 8 GPU is only 8.5 hours. ## Model Zoo | 骨架网络 | 网络类型 | 每张GPU图片个数 | 学习率策略 |推理时间(fps) | Box AP | 下载 | 配置文件 | | :-------------- | :------------- | :-----: | :-----: | :------------: | :-----: | :-----------------------------------------------------: | :-----: | | ResNet50-FPN | FCOS | 2 | 1x | ---- | 39.6 | [下载链接](https://paddledet.bj.bcebos.com/models/fcos_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/fcos/fcos_r50_fpn_1x_coco.yml) | | ResNet50-FPN | FCOS+DCN | 2 | 1x | ---- | 44.3 | [下载链接](https://paddledet.bj.bcebos.com/models/fcos_dcn_r50_fpn_1x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/fcos/fcos_dcn_r50_fpn_1x_coco.yml) | | ResNet50-FPN | FCOS+multiscale_train | 2 | 2x | ---- | 41.8 | [下载链接](https://paddledet.bj.bcebos.com/models/fcos_r50_fpn_multiscale_2x_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleDetection/tree/master/dygraph/configs/fcos/fcos_r50_fpn_multiscale_2x_coco.yml) | **Notes:** - FCOS is trained on COCO train2017 dataset and evaluated on val2017 results of `mAP(IoU=0.5:0.95)`. - FCOS training performace is dependented on Paddle develop branch, performance reproduction shoule based on [Paddle daily version](https://www.paddlepaddle.org.cn/documentation/docs/zh/install/Tables.html#whl-dev) or Paddle 2.0.1(will be published on 2021.03), performace will loss slightly is training base on Paddle 2.0.0 ## Citations ``` @inproceedings{tian2019fcos, title = {{FCOS}: Fully Convolutional One-Stage Object Detection}, author = {Tian, Zhi and Shen, Chunhua and Chen, Hao and He, Tong}, booktitle = {Proc. Int. Conf. Computer Vision (ICCV)}, year = {2019} } ```