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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

[email protected] 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)

selfie

Result on RetinaFace-MobileNetV2 (threshold=0.2)

retinaface

Result on CenterFace-MobileNetV2 (threshold=?)

selfie.centerface.draw.jpg

[email protected] Result on validation set of WiderFace

Train

train.md


Onnx And TensorRT

tensorRTIntegrate


QQ Group

936842116


Author

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