Age Estimation on UTKFace (test)
3.82MAEVOLO-D1 face
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| VOLO-D1 faceOutput=age & gender, Train Dataset=Lagenda train2023.07 | 3.82 | 72.64 | — | |
| VOLO-D1 faceOutput=age, Train Dataset=Lagenda train2023.07 | 3.9 | 72.25 | — | |
| LeRaCModel=CvT-13 (pre-trained)2022.05 | 4.06 | — | — | |
| VOLO-D1 faceOutput=age, Train Dataset=UTKFace, Released=true2023.07 | 4.23 | 69.72 | — | |
| VOLO-D1 faceOutput=age & gender, Train Dataset=UTKFace, Released=true2023.07 | 4.23 | 69.78 | — | |
| MWROutput=age, Train Dataset=UTKFace2023.07 | 4.37 | — | — | |
| Randomized BinsOutput=age, Train Dataset=UTKFace2023.07 | 4.55 | — | — | |
| CBSModel=CvT-13 (pre-trained)2022.05 | 4.61 | — | — | |
| conventionalModel=CvT-13 (pre-trained)2022.05 | 4.78 | — | — | |
| VOLO-D1 faceOutput=age & gender, Train Dataset=IMDB-clean, Released=true2023.07 | 5.15 | 56.79 | — | |
| GCLSSType=Semi-Supervised, Label ratio=1/10labels, Backbone=ResNet-502025.12 | 5.22 | — | 58.3 | |
| UCVMEType=Semi-Supervised, Label ratio=1/10labels, Backbone=ResNet-502025.12 | 5.26 | — | 57.9 | |
| CLSSType=Semi-Supervised, Label ratio=1/10labels, Backbone=ResNet-502025.12 | 5.26 | — | 58 | |
| VOLO-D1 faceOutput=age, Train Dataset=IMDB-clean, Released=true2023.07 | 5.28 | 56.79 | — | |
| CORALOutput=age, Train Dataset=UTKFace2023.07 | 5.39 | — | — | |
| CPSType=Semi-Supervised, Label ratio=1/10labels, Backbone=ResNet-502025.12 | 5.4 | — | 56.3 | |
| Mean-TeacherType=Supervised, Label ratio=1/10labels, Backbone=ResNet-502025.12 | 5.54 | — | 54.3 | |
| RankUpType=Semi-Supervised, Label ratio=1/10labels, Backbone=ResNet-502025.12 | 5.59 | — | 50.6 | |
| RegressionType=Supervised, Label ratio=1/10labels, Backbone=ResNet-502025.12 | 5.69 | — | 51 | |
| GCLSSType=Semi-Supervised, Label ratio=1/20labels, Backbone=ResNet-502025.12 | 5.72 | — | 52 | |
| CLSSType=Semi-Supervised, Label ratio=1/20labels, Backbone=ResNet-502025.12 | 5.79 | — | 51.1 | |
| UCVMEType=Semi-Supervised, Label ratio=1/20labels, Backbone=ResNet-502025.12 | 5.84 | — | 49.4 | |
| CPSType=Semi-Supervised, Label ratio=1/20labels, Backbone=ResNet-502025.12 | 5.92 | — | 47.9 | |
| RankUpType=Semi-Supervised, Label ratio=1/20labels, Backbone=ResNet-502025.12 | 5.92 | — | 47.8 | |
| LeRaCModel=ResNet-182022.05 | 5.97 | — | — | |
| Mean-TeacherType=Supervised, Label ratio=1/20labels, Backbone=ResNet-502025.12 | 6.15 | — | 45.7 | |
| GCLSSType=Semi-Supervised, Label ratio=1/30labels, Backbone=ResNet-502025.12 | 6.18 | — | 45.4 | |
| CLSSType=Semi-Supervised, Label ratio=1/30labels, Backbone=ResNet-502025.12 | 6.19 | — | 44.3 | |
| RegressionType=Supervised, Label ratio=1/20labels, Backbone=ResNet-502025.12 | 6.21 | — | 43.8 | |
| CBSModel=ResNet-182022.05 | 6.24 | — | — | |
| RankUpType=Semi-Supervised, Label ratio=1/30labels, Backbone=ResNet-502025.12 | 6.32 | — | 35.9 | |
| UCVMEType=Semi-Supervised, Label ratio=1/30labels, Backbone=ResNet-502025.12 | 6.43 | — | 41.4 | |
| conventionalModel=ResNet-182022.05 | 6.75 | — | — | |
| CPSType=Semi-Supervised, Label ratio=1/30labels, Backbone=ResNet-502025.12 | 6.99 | — | 34.8 | |
| Mean-TeacherType=Supervised, Label ratio=1/30labels, Backbone=ResNet-502025.12 | 7.04 | — | 32.6 | |
| RegressionType=Supervised, Label ratio=1/30labels, Backbone=ResNet-502025.12 | 7.92 | — | 27.1 |