paper-with-me

Age Estimation 벤치마크

Age Estimation on UTKFace

85개 결과 · ⬇ CSV · JSON

MAE 낮을수록 좋음

3.7 4.123 4.545 4.967 5.39 2019-01 2026-09 CORAL — 5.39 (2019-01-20) CORAL — 5.39 (2019-01-20) CORAL — 5.39 (2019-01-20) CORAL — 5.39 (2019-01-20) CORAL — 5.39 (2019-01-20) CORAL — 5.39 (2019-01-20) Randomized Bins — 4.55 (2020-06-29) Randomized Bins — 4.55 (2020-06-29) Randomized Bins — 4.55 (2020-06-29) Randomized Bins — 4.55 (2020-06-29) Randomized Bins — 4.55 (2020-06-29) Randomized Bins — 4.55 (2020-06-29) MWR — 4.37 (2022-03-24) MWR — 4.37 (2022-03-24) MWR — 4.37 (2022-03-24) MWR — 4.37 (2022-03-24) MWR — 4.37 (2022-03-24) MWR — 4.37 (2022-03-24) MiVOLO-D1 — 3.7 (2023-07-10) FaRL+MLP — 3.87 (2023-07-10) VOLO-D1 age&gender — 4.23 (2023-07-10) ResNet-50-SORD — 4.36 (2023-07-10) ResNet-50-Cross-Entropy — 4.38 (2023-07-10) ResNet-50-DLDL — 4.39 (2023-07-10) ResNet-50-OR-CNN — 4.4 (2023-07-10) ResNet-50-DLDL-v2 — 4.42 (2023-07-10) ResNet-50-Mean-Variance — 4.42 (2023-07-10) ResNet-50-Unimodal-Concentrated — 4.47 (2023-07-10) ResNet-50-Regression — 4.72 (2023-07-10) MiVOLO-D1 — 3.7 (2023-07-10) FaRL+MLP — 3.87 (2023-07-10) VOLO-D1 age&gender — 4.23 (2023-07-10) ResNet-50-SORD — 4.36 (2023-07-10) ResNet-50-Cross-Entropy — 4.38 (2023-07-10) ResNet-50-DLDL — 4.39 (2023-07-10) ResNet-50-OR-CNN — 4.4 (2023-07-10) ResNet-50-DLDL-v2 — 4.42 (2023-07-10) ResNet-50-Mean-Variance — 4.42 (2023-07-10) ResNet-50-Unimodal-Concentrated — 4.47 (2023-07-10) ResNet-50-Regression — 4.72 (2023-07-10) MiVOLO-D1 — 3.7 (2023-07-10) FaRL+MLP — 3.87 (2023-07-10) VOLO-D1 age&gender — 4.23 (2023-07-10) ResNet-50-SORD — 4.36 (2023-07-10) ResNet-50-Cross-Entropy — 4.38 (2023-07-10) ResNet-50-DLDL — 4.39 (2023-07-10) ResNet-50-OR-CNN — 4.4 (2023-07-10) ResNet-50-DLDL-v2 — 4.42 (2023-07-10) ResNet-50-Mean-Variance — 4.42 (2023-07-10) ResNet-50-Unimodal-Concentrated — 4.47 (2023-07-10) ResNet-50-Regression — 4.72 (2023-07-10) MiVOLO-D1 — 3.7 (2023-07-10) FaRL+MLP — 3.87 (2023-07-10) VOLO-D1 age&gender — 4.23 (2023-07-10) ResNet-50-SORD — 4.36 (2023-07-10) ResNet-50-Cross-Entropy — 4.38 (2023-07-10) ResNet-50-DLDL — 4.39 (2023-07-10) ResNet-50-OR-CNN — 4.4 (2023-07-10) ResNet-50-DLDL-v2 — 4.42 (2023-07-10) ResNet-50-Mean-Variance — 4.42 (2023-07-10) ResNet-50-Unimodal-Concentrated — 4.47 (2023-07-10) ResNet-50-Regression — 4.72 (2023-07-10) MiVOLO-D1 — 3.7 (2023-07-10) FaRL+MLP — 3.87 (2023-07-10) VOLO-D1 age&gender — 4.23 (2023-07-10) ResNet-50-SORD — 4.36 (2023-07-10) ResNet-50-Cross-Entropy — 4.38 (2023-07-10) ResNet-50-DLDL — 4.39 (2023-07-10) ResNet-50-OR-CNN — 4.4 (2023-07-10) ResNet-50-DLDL-v2 — 4.42 (2023-07-10) ResNet-50-Mean-Variance — 4.42 (2023-07-10) ResNet-50-Unimodal-Concentrated — 4.47 (2023-07-10) ResNet-50-Regression — 4.72 (2023-07-10) MiVOLO-D1 — 3.7 (2023-07-10) FaRL+MLP — 3.87 (2023-07-10) VOLO-D1 age&gender — 4.23 (2023-07-10) ResNet-50-SORD — 4.36 (2023-07-10) ResNet-50-Cross-Entropy — 4.38 (2023-07-10) ResNet-50-DLDL — 4.39 (2023-07-10) ResNet-50-OR-CNN — 4.4 (2023-07-10) ResNet-50-DLDL-v2 — 4.42 (2023-07-10) ResNet-50-Mean-Variance — 4.42 (2023-07-10) ResNet-50-Unimodal-Concentrated — 4.47 (2023-07-10) ResNet-50-Regression — 4.72 (2023-07-10) MobileAgeNet — 4.65 (2026-04-18) CORAL — 5.39 (2019-01-20) Randomized Bins — 4.55 (2020-06-29) MWR — 4.37 (2022-03-24) MiVOLO-D1 — 3.7 (2023-07-10)
RankModel MAE Extra Training Data PaperCodeYear
1 MiVOLO-D1 3.7 ✓ MiVOLO: Multi-input Transformer for Age and Gender Estimation wildchlamydia/mivolo · DILiS-lab/drivers-of-predictive-aleatoric-uncertainty 2023
2 FaRL+MLP 3.87 ✓ A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark paplhjak/facial-age-estimation-benchmark 2023
3 VOLO-D1 age&gender 4.23 MiVOLO: Multi-input Transformer for Age and Gender Estimation wildchlamydia/mivolo · DILiS-lab/drivers-of-predictive-aleatoric-uncertainty 2023
4 ResNet-50-SORD 4.36 ✓ A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark paplhjak/facial-age-estimation-benchmark 2023
5 MWR 4.37 Moving Window Regression: A Novel Approach to Ordinal Regression nhshin-mcl/mwr 2022
6 ResNet-50-Cross-Entropy 4.38 ✓ A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark paplhjak/facial-age-estimation-benchmark 2023
7 ResNet-50-DLDL 4.39 ✓ A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark paplhjak/facial-age-estimation-benchmark 2023
8 ResNet-50-OR-CNN 4.40 ✓ A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark paplhjak/facial-age-estimation-benchmark 2023
9 ResNet-50-DLDL-v2 4.42 ✓ A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark paplhjak/facial-age-estimation-benchmark 2023
9 ResNet-50-Mean-Variance 4.42 ✓ A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark paplhjak/facial-age-estimation-benchmark 2023
11 ResNet-50-Unimodal-Concentrated 4.47 ✓ A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark paplhjak/facial-age-estimation-benchmark 2023
12 Randomized Bins 4.55 Deep Ordinal Regression with Label Diversity axeber01/dold 2020
13 MobileAgeNet 자동 추출 4.65 MobileAgeNet: Lightweight Facial Age Estimation for Mobile Deployment 2026
14 ResNet-50-Regression 4.72 ✓ A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark paplhjak/facial-age-estimation-benchmark 2023
15 CORAL 5.39 Rank consistent ordinal regression for neural networks with application to age estimation Raschka-research-group/coral-cnn · ck37/coral-ordinal · axeber01/dold · +1 2019
16 MiVOLO-D1 3.7 ✓ MiVOLO: Multi-input Transformer for Age and Gender Estimation wildchlamydia/mivolo · DILiS-lab/drivers-of-predictive-aleatoric-uncertainty 2023
17 FaRL+MLP 3.87 ✓ A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark paplhjak/facial-age-estimation-benchmark 2023
18 VOLO-D1 age&gender 4.23 MiVOLO: Multi-input Transformer for Age and Gender Estimation wildchlamydia/mivolo · DILiS-lab/drivers-of-predictive-aleatoric-uncertainty 2023
19 ResNet-50-SORD 4.36 ✓ A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark paplhjak/facial-age-estimation-benchmark 2023
20 MWR 4.37 Moving Window Regression: A Novel Approach to Ordinal Regression nhshin-mcl/mwr 2022
1–20 / 85 다음 → 페이지당 10 20 50 100