Research map / Label-efficient and robust learning / Recognition and long-tail
Attributes for Improved Attributes: A Multi-Task Network Utilizing Implicit and Explicit Relationships for Facial Attribute Classification
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| share lower layers and group attributes in multi-task CNN (MCNN) vs independent CNNs (ablation) | attribute CNN · CelebA | accuracy: 90.95 -> 91.37 (Heavy Makeup) | Helped |
| multi-task MCNN vs independent CNNs (ablation) | attribute CNN · LFWA | accuracy: 92.15 -> 91.22 (Eyeglasses) | Mixed |
| add AUX score-level relationship network (ablation) | MCNN · CelebA | accuracy: 86.82 -> 86.63 (Necklace); 91.37 -> 91.55 (Heavy Makeup) | Mixed |
| multi-task MCNN instead of 40 independent CNNs | attribute CNN · CelebA | training time: 40 hours to 2.5 hours | Helped |
| independent CNNs without pretraining vs Liu et al. | attribute CNN · CelebA | accuracy: 84 -> 96.07 (Blurry) | Helped |
Closest papers by meaning
- Improving Facial Attribute Prediction Using Semantic Segmentation (CVPR 2017 · similarity 0.89)
- Fully-Adaptive Feature Sharing in Multi-Task Networks With Applications in Person Attribute Classification (CVPR 2017 · similarity 0.88)
- Automatic Discovery, Association Estimation and Learning of Semantic Attributes for a Thousand Categories (CVPR 2017 · similarity 0.88)
- Attributes Shape the Embedding Space of Face Recognition Models (ICML 2025 · similarity 0.87)
- SDGAN: Disentangling Semantic Manipulation for Facial Attribute Editing (AAAI 2024 · similarity 0.85)
- Distributionally Generative Augmentation for Fair Facial Attribute Classification (CVPR 2024 · similarity 0.84)
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