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SOTA
Altersschätzung
Age Estimation On Afad
Age Estimation On Afad
Metriken
MAE
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
MAE
Paper Title
CORAL
3.48
Rank consistent ordinal regression for neural networks with application to age estimation
ResNet-50-Unimodal-Concentrated
3.20
A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
ResNet-50-Regression
3.17
A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
ResNet-50-OR-CNN
3.16
A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
ResNet-50-Mean-Variance
3.16
A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
ResNet-50-DLDL-v2
3.15
A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
ResNet-50-DLDL
3.14
A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
ResNet-50-Cross-Entropy
3.14
A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
ResNet-50-SORD
3.14
A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
FaRL+MLP
3.12
A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
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Age Estimation On Afad | SOTA | HyperAI