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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

Backbone Model images/GPU lr schedule FPS Box AP download config
ResNet50-FPN FCOS 2 1x ---- 39.6 download config
ResNet50-FPN FCOS+DCN 2 1x ---- 44.3 download config
ResNet50-FPN FCOS+multiscale_train 2 2x ---- 41.8 download config

Notes:

  • FCOS is trained on COCO train2017 dataset and evaluated on val2017 results of mAP(IoU=0.5:0.95).

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}
}