CenterFace
Introduce
CenterFace(size of 7.3MB) is a practical anchor-free face detection and alignment method for edge devices.
Recent Update
2019.09.13CenterFace is released.
Environment
- OpenCV 4.1.0
- Numpy
- Python3.6+
Accuracy
- Results on val set of WIDER FACE:
| Model Version | Easy Set | Medium Set | Hard Set |
|---|---|---|---|
| FaceBoxes | 0.840 | 0.766 | 0.395 |
| FaceBoxes3.2× | 0.798 | 0.802 | 0.715 |
| RetinaFace-mnet | 0.896 | 0.871 | 0.681 |
| LFFD-v1 | 0.910 | 0.881 | 0.780 |
| LFFD-v2 | 0.837 | 0.835 | 0.729 |
| CenterFace | 0.935 | 0.924 | 0.875 |
| CenterFace-small | 0.931 | 0.924 | 0.870 |
- Results on test set of WIDER FACE:
| Model Version | Easy Set | Medium Set | Hard Set |
|---|---|---|---|
| FaceBoxes | 0.839 | 0.763 | 0.396 |
| FaceBoxes3.2× | 0.791 | 0.794 | 0.715 |
| RetinaFace-mnet | 0.896 | 0.871 | 0.681 |
| LFFD-v1 | 0.910 | 0.881 | 0.780 |
| LFFD-v2 | 0.837 | 0.835 | 0.729 |
| CenterFace | 0.932 | 0.921 | 0.873 |
- RetinaFace-mnet is short for RetinaFace-MobileNet-0.25 from excellent work insightface.
- LFFD-v1 is from prefect work LFFD.
- CenterFace/CenterFace-small evaluation is under MULTI-SCALE, FLIP.
- For SIO(Single Inference on the Original) evaluation schema, CenterFace also produces 92.2% (Easy), 91.1% (Medium) and 78.2% (Hard) for validation set.
- Results on FDDB:
| Model Version | Disc ROC curves score |
|---|---|
| RetinaFace-mnet | 96.0@1000 |
| LFFD-v1 | 97.3@1000 |
| LFFD-v2 | 97.2@1000 |
| CenterFace | 97.9@1000 |
| CenterFace-small | 98.1@1000 |
Inference Latency
- Latency on NVIDIA RTX 2080TI:
| Resolution-> | 640×480 | 1280×720(704) | 1920×1080(1056) |
|---|---|---|---|
| RetinaFace-mnet | 5.40ms | 6.31ms | 10.26ms |
| LFFD-v1 | 7.24ms | 14.58ms | 28.36ms |
| CenterFace | 5.5ms | 6.4ms | 8.7ms |
| CenterFace-small | 4.4ms | 5.7ms | 7.3ms |
Results: Face as Point
Discussion
Welcome to join in QQ Group(229042802) for more discussion, including but not limited to face detection, face anti-spoofing and so on.
Author
Citation
If you benefit from our work in your research and product, please consider to cite the following related papers:
@inproceedings{CenterFace,
title={CenterFace: Joint Face Detection and Alignment Using Face as Point},
author={Xu, Yuanyuan and Yan, Wan and Sun, Haixin and Yang, Genke and Luo, Jiliang},
booktitle={arXiv:1911.03599},
year={2019}
}
