insightface/model_zoo/README.md

InsightFace Model Zoo

0. Python Package models

To check the detail of insightface python package, please see here.

To install: pip install -U insightface

Name	Detection Model	Recognition Model	Alignment	Attributes
antelopev2	SCRFD-10GF	ResNet100@Glint360K	2d106 & 3d68	Gender&Age

1. Face Recognition models.

MFN: MobileFaceNet

MS1MV2: MS1M-ArcFace

MS1MV3: MS1M-RetinaFace

MegaFace: MegaFace identification test, with gallery=1e6.

IJBC: IJBC 1:1 test, under FAR<=1e-4.

BDrive: BaiduDrive

GDrive: GoogleDrive

ODrive: OneDrive

Backbone	Dataset	Method	LFW	CFP-FP	AgeDB-30	MegaFace	Link(mxnet)
R100	MS1MV2	ArcFace	99.77	98.27	98.28	98.47	BDrive
MFN	MS1MV1	ArcFace	99.50	88.94	95.91	-	BDrive

Backbone	Dataset	Method	LFW	CFP-FP	AgeDB-30	African	Caucasian	South Asian	East Asian	MR-All	link(onnx)
R100	Casia	ArcFace				39.666	53.933	47.807	21.572	42.735	download
R100	MS1MV2	ArcFace				79.117	87.176	85.501	55.807	80.725	download
R18	MS1MV3	ArcFace				62.613	75.125	70.213	43.859	68.326	download
R34	MS1MV3	ArcFace				71.644	83.291	80.084	53.712	77.365	download
R50	MS1MV3	ArcFace				75.488	86.115	84.305	57.352	80.533	download
R100	MS1MV3	ArcFace				81.083	89.040	88.082	62.193	84.312	download
R18	Glint360K	ArcFace				68.230	80.575	75.852	47.831	72.074	download
R34	Glint360K	ArcFace				79.907	88.620	86.815	60.604	83.015	download
R50	Glint360K	ArcFace				85.272	91.617	90.541	66.813	87.077	download
R100	Glint360K	ArcFace				89.488	94.285	93.434	72.528	90.659	download

+pfc: using Partial FC

Dataset	MR-ALL	African	Caucasian	South Asian	East Asian	LFW	CFP-FP	AgeDB-30	IJB-C(E4)	link(onnx)
CISIA	36.794	42.550	55.825	49.618	19.611	99.450	95.214	94.900	87.220
CISIA_pfc	37.107	38.934	53.823	48.674	19.927	99.367	95.429	94.600	84.970
VGG2	38.578	35.259	54.304	44.081	24.095	99.550	97.410	95.080	91.220
VGG2_pfc	40.673	36.767	60.180	49.039	24.255	99.683	98.529	95.400	92.490
GlintAsia	62.663	49.531	64.829	57.984	61.743	99.583	93.186	95.400	91.500
GlintAsia_pfc	63.149	50.366	65.227	57.936	61.820	99.650	93.029	95.233	91.140
MS1MV2	77.696	74.596	84.126	82.041	51.105	99.833	98.083	98.083	96.140
MS1MV2_pfc	77.738	74.728	84.883	82.798	52.507	99.783	98.071	98.017	96.080
MS1M_MegaFace	78.372	74.138	82.251	77.223	60.203	99.750	97.557	97.400	95.350
MS1M_MegaFace_pfc	78.773	73.690	82.947	78.793	57.566	99.800	97.870	97.733	95.400
MS1MV3	82.522	77.172	87.028	86.006	60.625	99.800	98.529	98.267	96.580
MS1MV3_pfc	81.683	78.126	87.286	85.542	58.925	99.800	98.443	98.167	96.430
Glint360k	86.789	84.749	91.414	90.088	66.168	99.817	99.143	98.450	97.130
Glint360k_pfc	87.077	85.272	91.616	90.541	66.813	99.817	99.143	98.450	97.020
WebFace12M	90.566	89.355	94.177	92.358	73.852	99.800	99.200	98.100	97.120
WebFace12M_pfc	89.951	89.301	94.016	92.381	73.007	99.817	99.143	98.117	97.010
Average	69.247	65.908	77.121	72.819	52.014	99.706	97.374	96.962	93.925
Average_pfc	69.519	65.898	77.497	73.213	51.853	99.715	97.457	96.965	93.818

2. Face Detection models.

2.1 RetinaFace

In RetinaFace, mAP was evaluated with multi-scale testing.

m025: means MobileNet-0.25

Impelmentation	Easy-Set	Medium-Set	Hard-Set	Link
RetinaFace-R50	96.5	95.6	90.4	BDrive, GDrive
RetinaFace-m025(yangfly)	-	-	82.5	BDrive(nzof), GDrive

2.2 SCRFD

In SCRFD, mAP was evaluated with single scale testing, VGA resolution.

2.5G: means the model cost 2.5G FLOPs while the input image is in VGA(640x480) resolution.

_KPS: means this model can detect five facial keypoints.

Name	Easy	Medium	Hard	FLOPs	Params(M)	Infer(ms)	Link
SCRFD_500M	90.57	88.12	68.51	500M	0.57	3.6	download
SCRFD_1G	92.38	90.57	74.80	1G	0.64	4.1	download
SCRFD_2.5G	93.78	92.16	77.87	2.5G	0.67	4.2	download
SCRFD_10G	95.16	93.87	83.05	10G	3.86	4.9	download
SCRFD_34G	96.06	94.92	85.29	34G	9.80	11.7	download
SCRFD_500M_KPS	90.97	88.44	69.49	500M	0.57	3.6	download
SCRFD_2.5G_KPS	93.80	92.02	77.13	2.5G	0.82	4.3	download
SCRFD_10G_KPS	95.40	94.01	82.80	10G	4.23	5.0	download

3. Face Alignment models.

2.1 2D Face Alignment

Impelmentation	Points	Backbone	Params(M)	Link(onnx)
Coordinate-regression	106	MobileNet-0.5	1.2	GDrive

2.2 3D Face Alignment

Impelmentation	Points	Backbone	Params(M)	Link(onnx)
-	68	ResNet-50	34.2	GDrive

2.3 Dense Face Alignment

4. Face Attribute models.

4.1 Gender&Age

Training-Set	Backbone	Params(M)	Link(onnx)
CelebA	MobileNet-0.25	0.3	GDrive

4.2 Expression