Gender Classification on UTKFace (test)
98.87Gender AccuracyVOLO-D1 face
Evaluation results
| Method | Links | ||||||
|---|---|---|---|---|---|---|---|
| VOLO-D1 faceOutput=age & gender, Train Dataset=Lagenda train2023.07 | 98.87 | — | — | — | — | — | |
| FairNVT2026.04 | 97.7 | 97.4 | 18.4 | 0.6 | 1.5 | 50.2 | |
| VOLO-D1 faceOutput=age & gender, Train Dataset=UTKFace, Released=true2023.07 | 97.69 | — | — | — | — | — | |
| VOLO-D1 faceOutput=age & gender, Train Dataset=IMDB-clean, Released=true2023.07 | 97.54 | — | — | — | — | — | |
| FairViT2026.04 | 97.5 | 97.1 | 21 | 1.8 | 1.1 | 81 | |
| ViT-FSCL2026.04 | 97.4 | 96.7 | 19.2 | 2.2 | 1.1 | 82.3 | |
| Vanilla2026.04 | 97.3 | 96 | 19.5 | 1.3 | 3.1 | 82.7 | |
| FairVPT2026.04 | 95.3 | 93.9 | 19.4 | 2 | 2 | 74.1 | |
| LeRaCModel=CvT-13 (pre-trained)2022.05 | 93.19 | — | — | — | — | — | |
| CBSModel=CvT-13 (pre-trained)2022.05 | 92.61 | — | — | — | — | — | |
| conventionalModel=CvT-13 (pre-trained)2022.05 | 92.57 | — | — | — | — | — | |
| LeRaCModel=ResNet-182022.05 | 90.07 | — | — | — | — | — | |
| CBSModel=ResNet-182022.05 | 89.23 | — | — | — | — | — | |
| conventionalModel=ResNet-182022.05 | 88.63 | — | — | — | — | — |