Research map / Label-efficient and robust learning / Semi-supervised learning
Semi-Supervised Adaptive Label Distribution Learning for Facial Age Estimation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add unlabeled data via semi-supervised process (SLDL/SALDL vs ALDL) (ablation) | ALDL · MORPH, <1,000 labeled images | MAE | Helped |
| add label distribution adaptation (SALDL vs SLDL) (ablation) | SLDL · MORPH | MAE | Helped |
| adaptation steps of ALDL with only 500 labeled images (ablation) | ALDL · MORPH, 500 labeled images | MAE | Hurt |
| SALDL vs general semi-supervised Label Propagation | SALDL · MORPH, 100 labeled images | labeled images needed to match MAE: 30,000 -> 100 | Helped |
| SALDL vs LDL | SALDL · MORPH, 100 labeled images | labeled images needed to match MAE: 2,000 -> 100 | Helped |
| more labeled images beyond 10,000 | SALDL · MORPH | MAE | No clear effect |
| add unlabeled images from different race or gender | SALDL · MORPH, 500 labeled images | MAE | Helped |
Closest papers by meaning
- Unimodal-Concentrated Loss: Fully Adaptive Label Distribution Learning for Ordinal Regression (CVPR 2022 · similarity 0.87)
- A Call to Reflect on Evaluation Practices for Age Estimation: Comparative Analysis of the State-of-the-Art and a Unified Benchmark (CVPR 2024 · similarity 0.85)
- From Cradle to Cane: A Two-Pass Framework for High-Fidelity Lifespan Face Aging (NeurIPS 2025 · similarity 0.82)
- Approximately Correct Label Distribution Learning (ICML 2025 · similarity 0.82)
- InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-Supervised Learning (ICML 2024 · similarity 0.81)
- AQUAFace: Age-Invariant Quality Adaptive Face Recognition for Unconstrained Selfie vs ID Verification (AAAI 2025 · similarity 0.81)
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