HyperAI超神经

Age Estimation On Chalearn 2015

评估指标

e-error

评测结果

各个模型在此基准测试上的表现结果

		Paper Title
DLDL+VGG-Face	0.31	Deep Label Distribution Learning with Label Ambiguity
DLDL-v2 (ThinAgeNet)	0.272	Learning Expectation of Label Distribution for Facial Age and Attractiveness Estimation
AgeNet	0.270685	AgeNet: Deeply Learned Regressor and Classifier for Robust Apparent Age Estimation
DEX	0.264975	Deep Expectation of Real and Apparent Age from a Single Image Without Facial Landmarks
BridgeNet	0.255140	BridgeNet: A Continuity-Aware Probabilistic Network for Age Estimation
MetaAge	0.250651	MetaAge: Meta-Learning Personalized Age Estimators
MWR	-	Moving Window Regression: A Novel Approach to Ordinal Regression

0 of 7 row(s) selected.

HyperAI超神经

Age Estimation On Chalearn 2015

评估指标

e-error

评测结果

各个模型在此基准测试上的表现结果

		Paper Title
DLDL+VGG-Face	0.31	Deep Label Distribution Learning with Label Ambiguity
DLDL-v2 (ThinAgeNet)	0.272	Learning Expectation of Label Distribution for Facial Age and Attractiveness Estimation
AgeNet	0.270685	AgeNet: Deeply Learned Regressor and Classifier for Robust Apparent Age Estimation
DEX	0.264975	Deep Expectation of Real and Apparent Age from a Single Image Without Facial Landmarks
BridgeNet	0.255140	BridgeNet: A Continuity-Aware Probabilistic Network for Age Estimation
MetaAge	0.250651	MetaAge: Meta-Learning Personalized Age Estimators
MWR	-	Moving Window Regression: A Novel Approach to Ordinal Regression

0 of 7 row(s) selected.

Age Estimation On Chalearn 2015 | SOTA | HyperAI超神经