CenterFace
Introduce
CenterFace(size of 7.3MB, and AP 88.0% on the WIDER FACE hard set) is a practical anchor-free face detector for edge devices. CenterFace-small achieving AP equal to CenterFace while model size is only 2.3M.
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 |
|---|---|---|---|
| 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 | 0.939 | 0.929 | 0.880 |
| CenterFace-small | 0.931 | 0.924 | 0.870 |
- 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.
- 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 |
Joint face detection and alignment By CenterFace
We also try the mutil-task Center Face to joint face detection and alignment. The model is releasing soon.
Results
Discussion
Welcome to join in QQ Group(912759877) for more discussion, including but not limited to face detection, face anti-spoofing and so on.