Research map / Label-efficient and robust learning / Domain adaptation and generalization
Dual Distribution Alignment Network for Generalizable Person Re-Identification
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add triplet loss to IDE training (ablation) | DDAN · VIPeR, PRID, GRID, i-LIDS | Rank-1 accuracy: 41.4 -> 47.2; 30.8 -> 46.4; 38.1 -> 45.3; 66.2 -> 72.3 | Helped |
| Add domain-wise adversarial alignment (ablation) | IDE+Triplet · VIPeR, PRID, GRID, i-LIDS | Rank-1 accuracy: 47.2 -> 50.6; 46.4 -> 50.0; 45.3 -> 47.6; 72.3 -> 74.6 | Helped |
| Add identity-wise similarity enhancement (ablation) | IDE+Triplet+DA · VIPeR, PRID, GRID, i-LIDS | Rank-1 accuracy: 50.6 -> 52.3; 50.0 -> 54.5; 47.6 -> 50.6; 74.6 -> 78.5 | Helped |
| Integrate DualNorm into DDAN | DDAN · VIPeR, PRID, GRID, i-LIDS | Rank-1 accuracy: 52.3 -> 56.5; 54.5 -> 62.9; 50.6 -> 46.2; 78.5 -> 78.0 | Mixed |
| Use PersonSearch rather than Duke as the central domain (ablation) | Baseline + domain-wise alignment · PRID | Rank-1 accuracy: 47.3 -> 50.0 | Helped |
| Use pairwise alignment across all source domains instead of selecting a central domain (ablation) | Baseline + domain-wise alignment · VIPeR, PRID, GRID, i-LIDS | Rank-1 accuracy: 50.6 -> 48.7; 50.0 -> 45.4; 47.6 -> 44.2; 74.6 -> 74.5 | Hurt |
| Enable similarity enhancement with k greater than zero instead of disabling it at k=0 (ablation) | DDAN · Target datasets | Rank-1 accuracy | Helped |
| Use an excessively large number of similar IDs (ablation) | DDAN · Target datasets | Rank-1 accuracy | Hurt |
| Set temperature to a very small value such as 2*10^-5 (ablation) | DDAN · Training | Convergence | Hurt |
Closest papers by meaning
- Meta Distribution Alignment for Generalizable Person Re-Identification (CVPR 2022 · similarity 0.91)
- Generalizable Person Re-identification via Balancing Alignment and Uniformity (NeurIPS 2024 · similarity 0.91)
- Generalizable Person Re-Identification by Domain-Invariant Mapping Network (CVPR 2019 · similarity 0.90)
- Unsupervised Domain Adaptation for Person Re-identification via Heterogeneous Graph Alignment (AAAI 2021 · similarity 0.90)
- Diversity-Authenticity Co-constrained Stylization for Federated Domain Generalization in Person Re-identification (AAAI 2024 · similarity 0.86)
- Domain Generalizable Person Search Using Unreal Dataset (AAAI 2024 · similarity 0.86)
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