Age Estimation On Afad

Metrics

MAE

Results

Performance results of various models on this benchmark

		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

0 of 10 row(s) selected.

Age Estimation On Afad

Metrics

MAE

Results

Performance results of various models on this benchmark

		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

0 of 10 row(s) selected.

Age Estimation On Afad | SOTA | HyperAI