Research map / Video / Video segmentation and tracking
Walk and Learn: Facial Attribute Representation Learning From Egocentric Video and Contextual Data
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Pre-train with identity verification on Ego-Humans face pairs instead of random initialization (ablation) | Base network for facial attribute classification · Wearable facial attributes | Average accuracy: 82 -> 87 | Helped |
| Add geo-location features to identity-verification features (ablation) | Facial attribute representation · Wearable facial attributes | Average accuracy: +2% | Helped |
| Add weather features to identity-verification features (ablation) | Facial attribute representation · Wearable facial attributes | Average accuracy: +2% | Helped |
| Add both weather and geo-location features to identity-verification features (ablation) | Facial attribute representation · Wearable facial attributes | Average accuracy: +4% | Helped |
| Use the proposed representation rather than LNet+ANet | Facial attribute classification · LFWA | Average accuracy: 84 -> 87 | Helped |
| Use the proposed representation rather than LNet+ANet | Facial attribute classification · CelebA | Average accuracy: 87 -> 88 | Helped |
Closest papers by meaning
- Pedestrian Attribute Recognition: A New Benchmark Dataset and a Large Language Model Augmented Framework (AAAI 2025 · similarity 0.84)
- Fusing Personal and Environmental Cues for Identification and Segmentation of First-Person Camera Wearers in Third-Person Views (CVPR 2024 · similarity 0.84)
- EgoSim: An Egocentric Multi-view Simulator and Real Dataset for Body-worn Cameras during Motion and Activity (NeurIPS 2024 · similarity 0.83)
- Attributes Shape the Embedding Space of Face Recognition Models (ICML 2025 · similarity 0.83)
- PairDETR : Joint Detection and Association of Human Bodies and Faces (CVPR 2024 · similarity 0.83)
- Selective and Orthogonal Feature Activation for Pedestrian Attribute Recognition (AAAI 2024 · similarity 0.83)
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