DBFace | 中文说明 | ncnn支持

DBFace is a real-time, single-stage detector for face detection, with faster speed and higher accuracy

MAP@0.5 Result on validation set of WiderFace

• Single Scale Inference on the Original Image

Method	Version	Size	Easy	Medium	Hard
RetinaFace-MobileNetV2	Small	1.68MB	0.896	0.871	0.681
DBFace-Small-H-NoExt(Ours)	Small	1.30MB	0.895	0.870	0.713
DBFace-Small-H(Ours)	Small	1.73MB	0.899	0.876	0.728
DBFace-MobileNetV3 (Ours)	Large	7.03MB	0.905	0.896	0.794
CenterFace-MobileNetV2	Large	7.3MB	?	?	?

Result on DBFace (threshold = 0.2)

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Result on RetinaFace-MobileNetV2 (threshold=0.2)

• link.retinaface

Result on CenterFace-MobileNetV2 (threshold=?)

• link.centerface

MAP@0.5 Result on validation set of WiderFace

Train

train.md

Onnx And TensorRT

tensorRTIntegrate

QQ Group

936842116

Author

• liuanqi-libra7
• dlunion

References

1. Hamid Rezatofighi1, Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression：https://arxiv.org/abs/1902.09630

2. Xingyi Zhou, Objects as Points：https://arxiv.org/abs/1904.07850

3. Zili Liu, Training-Time-Friendly Network for Real-Time Object Detection：https://arxiv.org/abs/1909.00700

4. Zhen-Hua Feng, Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks: https://arxiv.org/abs/1711.06753v4

5. Mahyar Najib, SSH: Single Stage Headless Face Detector: https://arxiv.org/abs/1708.03979

6. MobileNet: https://github.com/xiaolai-sqlai/mobilenetv3