Research map / Label-efficient and robust learning / Recognition and long-tail
Diverse Part Discovery: Occluded Person Re-Identification With Part-Aware Transformer
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the pixel-context encoder with global feature only (ablation) | PAT · Occluded-Duke | mAP: 38.8 -> 45.9 | Helped |
| Add part-prototype decoder with self- and cross-attention (ablation) | PAT · Occluded-Duke | mAP: +12.9% | Helped |
| Add pixel-context encoder to the part decoder (ablation) | PAT · Occluded-Duke | mAP: 51.7 -> 52.5 | Helped |
| Add self-attention among part prototypes (ablation) | PAT · Occluded-Duke | mAP: +0.9% | Helped |
| Add part diversity loss (ablation) | PAT · Occluded-Duke | mAP: 52.5 -> 53.6 | Helped |
| Increase the number of part prototypes (ablation) | PAT · Occluded-Duke | Rank-1 | Helped |
| Set the number of part prototypes to 6 (ablation) | PAT · Market-1501 | Rank-1 | Mixed |
| Use PAT instead of ISP | Person Re-ID · Occluded-Duke | Rank-1: 62.8 -> 64.5 | Helped |
| Use PAT instead of HOReID | Person Re-ID · Partial-REID | Rank-1: +2.7% | Helped |
| Use PAT instead of HOReID | Person Re-ID · Partial-iLIDS | Rank-1: +3.9% | Helped |
Closest papers by meaning
- Partial Person Re-Identification With Part-Part Correspondence Learning (CVPR 2021 · similarity 0.88)
- Pose-Guided Feature Disentangling for Occluded Person Re-identification Based on Transformer (AAAI 2022 · similarity 0.88)
- Dynamic Feature Pruning and Consolidation for Occluded Person Re-identification (AAAI 2024 · similarity 0.88)
- PSTR: End-to-End One-Step Person Search With Transformers (CVPR 2022 · similarity 0.87)
- From Poses to Identity: Training-Free Person Re-Identification via Feature Centralization (CVPR 2025 · similarity 0.85)
- Attention Disturbance and Dual-Path Constraint Network for Occluded Person Re-identification (AAAI 2024 · similarity 0.85)
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