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Continuous Face Aging via Self-Estimated Residual Age Embedding
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use self-estimated continuous age embeddings instead of interpolation between anchor age groups | Face aging · FFHQ, continuous aging | aging accuracy | Helped |
| Use personalized residual age embedding in the target age embedding (ablation) | Continuous face aging model · Face aging examples | personalized trait preservation and visual artifacts | Helped |
| Add the target-age shift coefficient βφ (ablation) | Personalized age embedding transformation · Face aging | performance | No clear effect |
| Use the proposed method rather than S²GAN | Face aging · CACD2000 | face verification rate: 98.91% -> 99.97% | Helped |
| Use the proposed method rather than Lifespan | Face aging · FFHQ | face verification rate: 87.11% -> 99.98% | Helped |
| Use the proposed method rather than S²GAN | Face aging · CACD2000 | FID: 8.4 -> 6.7 | Helped |
| Use the proposed method rather than Lifespan | Face aging · FFHQ | FID: 26.2 -> 18.5 | Helped |
| Use the proposed method rather than Lifespan | Face aging · FFHQ age group 30-39 | mean generated age: 38.4 -> 38.4 | No clear effect |
Closest papers by meaning
- Learning Face Age Progression: A Pyramid Architecture of GANs (CVPR 2018 · similarity 0.94)
- Face Aging With Identity-Preserved Conditional Generative Adversarial Networks (CVPR 2018 · similarity 0.93)
- Age Progression and Regression with Spatial Attention Modules (AAAI 2020 · similarity 0.92)
- Attribute-Aware Face Aging With Wavelet-Based Generative Adversarial Networks (CVPR 2019 · similarity 0.91)
- From Cradle to Cane: A Two-Pass Framework for High-Fidelity Lifespan Face Aging (NeurIPS 2025 · similarity 0.88)
- 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 0.86)
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