Age Estimation on Chalearn LAP 2015 (val)
0.292ErrorICT-VIPL
Evaluation results
| Method | Links | ||
|---|---|---|---|
| ICT-VIPL2016.11 | 0.292 | — | |
| All-In-One CNN2016.11 | 0.293 | — | |
| CVL_ETHZ2016.11 | 0.295 | — | |
| CascadeAge2016.11 | 0.297 | — | |
| Human2016.11 | 0.34 | — | |
| UMD2016.11 | 0.359 | — | |
| MWR2022.03 | 2.95 | 0.26 | |
| BridgeNetPretrain Set=IMDB-WIKI, Network=VGG-16, # of Networks=12019.04 | 2.98 | 0.26 | |
| BridgeNet2022.03 | 2.98 | 0.26 | |
| AL-RoR-34Backbone=RoR-342018.05 | 3.137 | 0.2683 | |
| ARN2018.05 | 3.153 | — | |
| Tan et al.Pretrain Set=IMDB-WIKI, Network=VGG-16, # of Networks=82019.04 | 3.21 | 0.28 | |
| AGEn2022.03 | 3.21 | 0.28 | |
| DEX22018.05 | 3.221 | 0.278 | |
| AL-ResNets-152Backbone=ResNet-1522018.05 | 3.243 | 0.2778 | |
| CVL_ETHZPretrain Set=IMDB-WIKI, Network=VGG-16, # of Networks=202019.04 | 3.25 | 0.28 | |
| DEX2022.03 | 3.25 | 0.28 | |
| DEX12018.05 | 3.252 | 0.282 | |
| Rich Coding2018.05 | 3.29 | 0.3273 | |
| ICT-VIPLPretrain Set=MORPH, CACD, et al., Network=GoogleNet, # of Networks=82019.04 | 3.33 | 0.29 | |
| AgeNet2022.03 | 3.33 | 0.29 | |
| AgeNet2018.05 | 3.334 | 0.2922 | |
| AL-ResNets-34Backbone=ResNet-342018.05 | 3.357 | 0.281 | |
| ResNets-34Backbone=ResNet-342018.05 | 3.712 | 0.3167 | |
| Logit Boost2018.05 | 7.2949 | 0.5483 | |
| age group2018.05 | — | 0.3162 | |
| DADL2018.05 | — | 0.3806 | |
| SEU_NJUPretrain Set=FG-NET, MORPH, et al., Network=GoogleNet, # of Networks=62019.04 | — | 0.34 | |
| WVU_CVLPretrain Set=MORPH, CACD, et al., Network=GoogleNet, # of Networks=52019.04 | — | 0.31 | |
| Zhu et al.2022.03 | — | 0.31 |