在yolov5的基础上增加landmark预测分支，loss使用wingloss,使用yolov5s取得了相对于retinaface-r50更好的性能。
- 在wider face val精度（单尺度最大边输入分辨率：1024）
| Backbone | Easy | Medium | Hard |
|---|---|---|---|
| yolov5s | 95.4% | 94.6% | 88.2% |
| Yolov5m | 95.8% | 95.1% | 90.5% |
| RetinaFace-R50(original image scale) | 95.5% | 94.0% | 84.4% |
- yolov5s:链接: https://pan.baidu.com/s/1t51CFeofy1slOw_lgb3UDg 密码: mkh0
- Yolov5m:
https://github.com/ultralytics/yolov5
https://github.com/DayBreak-u/yolo-face-with-landmark