PaddleDetection/configs/fcos

• FCOS for Object Detection
• • Introduction
  • Model Zoo
  • Citations

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}
}