Awesome
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)
Result on RetinaFace-MobileNetV2 (threshold=0.2)
Result on CenterFace-MobileNetV2 (threshold=?)
MAP@0.5 Result on validation set of WiderFace
Train
<br/>Onnx And TensorRT
<br/>QQ Group
936842116
<br/>Author
References
-
Hamid Rezatofighi1, Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression：https://arxiv.org/abs/1902.09630
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Xingyi Zhou, Objects as Points：https://arxiv.org/abs/1904.07850
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Zili Liu, Training-Time-Friendly Network for Real-Time Object Detection：https://arxiv.org/abs/1909.00700
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Zhen-Hua Feng, Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks: https://arxiv.org/abs/1711.06753v4
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Mahyar Najib, SSH: Single Stage Headless Face Detector: https://arxiv.org/abs/1708.03979
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MobileNet: https://github.com/xiaolai-sqlai/mobilenetv3