Research map / Graph learning / Knowledge and temporal graphs
Context-Aware Graph Convolution Network for Target Re-identification
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use CAGCN context reasoning instead of the baseline feature model | Re-identification model · Market1501 | mAP: 85.4 -> 91.6 | Helped |
| Use CAGCN context reasoning instead of the baseline feature model | Re-identification model · DukeMTMC-reID | mAP: 75.6 -> 85.4 | Helped |
| Use CAGCN context reasoning instead of the baseline feature model | Re-identification model · VeRi-776 | mAP: 74.1 -> 79.2 | Helped |
| Use hard gallery sampler rather than plain nearest-neighbor sampling (ablation) | CAGCN · Market1501 | mAP: 90.4 -> 91.6 | Helped |
| Use hard gallery sampler rather than plain nearest-neighbor sampling (ablation) | CAGCN · DukeMTMC-reID | mAP: 83.1 -> 85.4 | Helped |
| Use hard gallery sampler rather than plain nearest-neighbor sampling (ablation) | CAGCN · VeRi-776 | mAP: 78.1 -> 79.2 | Helped |
| Increase graph size from 100 to 500 nodes (ablation) | CAGCN · Market1501 | mAP: 91.6 -> 91.7 | No clear effect |
| Increase graph depth from 3 to 9 GCN layers (ablation) | CAGCN · Market1501 | mAP: 88.4 -> 91.6 | Helped |
| Increase graph neighbors per node from 8 to 50 (ablation) | CAGCN · Market1501 | mAP: 91.6 -> 89.9 | Hurt |
| Add re-ranking post-processing | CAGCN · Market1501 | mAP: 91.7 -> 94 | Helped |
| Add re-ranking post-processing | CAGCN · DukeMTMC-reID | mAP: 85.9 -> 88.9 | Helped |
Closest papers by meaning
- Learning Context Graph for Person Search (CVPR 2019 · similarity 0.90)
- Spatial-Temporal Graph Convolutional Network for Video-Based Person Re-Identification (CVPR 2020 · similarity 0.87)
- Person Re-Identification Using Heterogeneous Local Graph Attention Networks (CVPR 2021 · similarity 0.86)
- Cheb-GR: Rethinking K-nearest Neighbor Search in Re-ranking for Person Re-identification (CVPR 2025 · similarity 0.85)
- Locality-Aware Graph Rewiring in GNNs (ICLR 2024 · similarity 0.84)
- CLIP-driven View-aware Prompt Learning for Unsupervised Vehicle Re-identification (AAAI 2025 · similarity 0.83)
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