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Age Estimation On Afad

Metrics

MAE

Results

Performance results of various models on this benchmark

Paper TitleRepository
CORAL3.48Rank consistent ordinal regression for neural networks with application to age estimation
ResNet-50-Unimodal-Concentrated3.20A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
ResNet-50-Regression3.17A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
ResNet-50-OR-CNN3.16A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
ResNet-50-Mean-Variance3.16A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
ResNet-50-DLDL-v23.15A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
ResNet-50-DLDL3.14A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
ResNet-50-Cross-Entropy3.14A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
ResNet-50-SORD3.14A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark
FaRL+MLP3.12A 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