Focal Loss for Dense Object Detection
Introduction
@inproceedings{lin2017focal,
title={Focal loss for dense object detection},
author={Lin, Tsung-Yi and Goyal, Priya and Girshick, Ross and He, Kaiming and Doll{\'a}r, Piotr},
booktitle={Proceedings of the IEEE international conference on computer vision},
year={2017}
}
Results and models
| Backbone |
Style |
Lr schd |
Mem (GB) |
Inf time (fps) |
box AP |
Download |
| R-50-FPN |
caffe |
1x |
3.5 |
18.6 |
36.3 |
model | log |
| R-50-FPN |
pytorch |
1x |
3.8 |
19.0 |
36.5 |
model | log |
| R-50-FPN |
pytorch |
2x |
- |
- |
37.4 |
model | log |
| R-101-FPN |
caffe |
1x |
5.5 |
14.7 |
38.5 |
model | log |
| R-101-FPN |
pytorch |
1x |
5.7 |
15.0 |
38.5 |
model | log |
| R-101-FPN |
pytorch |
2x |
- |
- |
38.9 |
model | log |
| X-101-32x4d-FPN |
pytorch |
1x |
7.0 |
12.1 |
39.9 |
model | log |
| X-101-32x4d-FPN |
pytorch |
2x |
- |
- |
40.1 |
model | log |
| X-101-64x4d-FPN |
pytorch |
1x |
10.0 |
8.7 |
41.0 |
model | log |
| X-101-64x4d-FPN |
pytorch |
2x |
- |
- |
40.8 |
model | log |