ZF/insightface
1
0
Fork 0
mirror of https://github.com/deepinsight/insightface.git synced 2026-05-21 09:07:48 +00:00
Code Issues Packages Projects Releases Wiki Activity
Files
65a2dccdb6bd7bac275cfeffc54160dcf4e69d6f
insightface/model_zoo/README.md
Jia Guo 65a2dccdb6 Update README.md
2021-08-04 23:21:15 +08:00

133 lines
9.7 KiB
Markdown
Raw Blame History

# InsightFace Model Zoo
## 0. Python Package models
To check the detail of insightface python package, please see [here](../python-package).
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](https://pan.baidu.com/s/1wuRTf2YIsKt76TxFufsRNA) |
| MFN | MS1MV1 | ArcFace | 99.50 | 88.94 | 95.91 | - | [BDrive](https://pan.baidu.com/s/1If28BkHde4fiuweJrbicVA) |
| 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](https://1drv.ms/u/s!AswpsDO2toNKrUJpk8zC61HVN7Kg?e=zE9JDd) |
| R100 | MS1MV2 | ArcFace | | | | 79.117 | 87.176 | 85.501 | 55.807 | 80.725 | [download](https://1drv.ms/u/s!AswpsDO2toNKrUTlYEHJCHg3UYM-?e=ihxMpS) |
| R18 | MS1MV3 | ArcFace | | | | 62.613 | 75.125 | 70.213 | 43.859 | 68.326 | [download](https://1drv.ms/u/s!AswpsDO2toNKrTxlT6w1Jo02yzSh?e=KDhFAA) |
| R34 | MS1MV3 | ArcFace | | | | 71.644 | 83.291 | 80.084 | 53.712 | 77.365 | [download](https://1drv.ms/u/s!AswpsDO2toNKrT2O5pgyVtwnjeMq?e=16S8LI) |
| R50 | MS1MV3 | ArcFace | | | | 75.488 | 86.115 | 84.305 | 57.352 | 80.533 | [download](https://1drv.ms/u/s!AswpsDO2toNKrUUWd5i3a5OlFpM_?e=ExBDBN) |
| R100 | MS1MV3 | ArcFace | | | | 81.083 | 89.040 | 88.082 | 62.193 | 84.312 | [download](https://1drv.ms/u/s!AswpsDO2toNKrUPwyqWvNXUlNd3P?e=pTLw9A) |
| R18 | Glint360K | ArcFace | | | | 68.230 | 80.575 | 75.852 | 47.831 | 72.074 | [download](https://1drv.ms/u/s!AswpsDO2toNKrT5ey4lCqFzlpzDd?e=VWP28J) |
| R34 | Glint360K | ArcFace | | | | 79.907 | 88.620 | 86.815 | 60.604 | 83.015 | [download](https://1drv.ms/u/s!AswpsDO2toNKrUBcgGkiuUS11Hsd?e=ISGDnP) |
| R50 | Glint360K | ArcFace | | | | 85.272 | 91.617 | 90.541 | 66.813 | 87.077 | [download](https://1drv.ms/u/s!AswpsDO2toNKrT8jbvHxjqCY0d08?e=igfdrd) |
| R100 | Glint360K | ArcFace | | | | 89.488 | 94.285 | 93.434 | 72.528 | 90.659 | [download](https://1drv.ms/u/s!AswpsDO2toNKrUFgLEIj-mnkb51b?e=vWqy2q) |
``+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](https://pan.baidu.com/s/1C6nKq122gJxRhb37vK0_LQ), [GDrive](https://drive.google.com/file/d/1wm-6K688HQEx_H90UdAIuKv-NAsKBu85/view?usp=sharing) |
| RetinaFace-m025(yangfly) | - | - | 82.5 | [BDrive](https://pan.baidu.com/s/1P1ypO7VYUbNAezdvLm2m9w)(nzof), [GDrive](https://drive.google.com/drive/folders/1OTXuAUdkLVaf78iz63D1uqGLZi4LbPeL?usp=sharing) |
### 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](https://1drv.ms/u/s!AswpsDO2toNKqyYWxScdiTITY4TQ?e=DjXof9) |
| SCRFD_1G | 92.38 | 90.57 | 74.80 | 1G | 0.64 | 4.1 | [download](https://1drv.ms/u/s!AswpsDO2toNKqyPVLI44ahNBsOMR?e=esPrBL) |
| SCRFD_2.5G | 93.78 | 92.16 | 77.87 | 2.5G | 0.67 | 4.2 | [download](https://1drv.ms/u/s!AswpsDO2toNKqyTIXnzB1ujPq4th?e=5t1VNv) |
| SCRFD_10G | 95.16 | 93.87 | 83.05 | 10G | 3.86 | 4.9 | [download](https://1drv.ms/u/s!AswpsDO2toNKqyUKwTiwXv2kaa8o?e=umfepO) |
| SCRFD_34G | 96.06 | 94.92 | 85.29 | 34G | 9.80 | 11.7 | [download](https://1drv.ms/u/s!AswpsDO2toNKqyKZwFebVlmlOvzz?e=V2rqUy) |
| SCRFD_500M_KPS | 90.97 | 88.44 | 69.49 | 500M | 0.57 | 3.6 | [download](https://1drv.ms/u/s!AswpsDO2toNKri_NDM0GIkPpkE2f?e=JkebJo) |
| SCRFD_2.5G_KPS | 93.80 | 92.02 | 77.13 | 2.5G | 0.82 | 4.3 | [download](https://1drv.ms/u/s!AswpsDO2toNKqyGlhxnCg3smyQqX?e=A6Hufm) |
| SCRFD_10G_KPS | 95.40 | 94.01 | 82.80 | 10G | 4.23 | 5.0 | [download](https://1drv.ms/u/s!AswpsDO2toNKqycsF19UbaCWaLWx?e=F6i5Vm) |
## 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](https://drive.google.com/file/d/1M5685m-bKnMCt0u2myJoEK5gUY3TDt_1/view?usp=sharing) |
### 2.2 3D Face Alignment
| Impelmentation | Points | Backbone | Params(M) | Link(onnx) |
| -------------- | ------ | --------- | --------- | ------------------------------------------------------------ |
| - | 68 | ResNet-50 | 34.2 | [GDrive](https://drive.google.com/file/d/1aJe5Rzoqrtf_a9U84E-V1b0rUi8-QbCI/view?usp=sharing) |
### 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](https://drive.google.com/file/d/1Mm3TeUuaZOwmEMp0nGOddvgXCjpRodPU/view?usp=sharing) |
### 4.2 Expression
Reference in New Issue View Git Blame Copy Permalink