Research map / Graph learning / Graph self-supervised learning
SIGMA: Semantic-Complete Graph Matching for Domain Adaptive Object Detection
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use semantic-complete graphs and bipartite graph matching rather than prototype-only category alignment | SIGMA · Cityscapes→Foggy Cityscapes | mAP: 43.5 vs 41.7 | Helped |
| Add Domain-guided Node Completion (ablation) | SIGMA GSC · Cityscapes→Foggy Cityscapes | mAP: 40.4 -> 41.8 | Helped |
| Use the graph-guided memory bank instead of a common buffer (ablation) | SIGMA GSC · Cityscapes→Foggy Cityscapes | mAP: 41.0 -> 41.8 | Helped |
| Add the Node Discriminator (ablation) | SIGMA GSC · Cityscapes→Foggy Cityscapes | mAP: 39.4 -> 41.8 | Helped |
| Add Cross Graph Interaction (ablation) | SIGMA BGM · Cityscapes→Foggy Cityscapes | mAP: 42.8 -> 43.5 | Helped |
| Use semantic-aware node affinity instead of simplified affinity (ablation) | SIGMA BGM · Cityscapes→Foggy Cityscapes | mAP: 42.6 -> 43.5 | Helped |
| Add Structure-aware Matching Loss (ablation) | SIGMA BGM · Cityscapes→Foggy Cityscapes | mAP: 42.2 -> 43.5 | Helped |
| Use 200 nodes from both domains rather than 100 (ablation) | SIGMA · Cityscapes→Foggy Cityscapes | mAP: 43.5 -> 43.9 | Helped |
| Increase sampled nodes to 500 per domain (ablation) | SIGMA · Cityscapes→Foggy Cityscapes | mAP: 43.9 -> 42.6 | Hurt |
| Add False-positive Suppression to True-positive Enhancement (ablation) | Single-matching loss · Cityscapes→Foggy Cityscapes | mAP@0.5:0.95: 22.0 -> 23.8 | Helped |
| Add Quadratic Constraints to TE and FS (ablation) | Single-matching loss · Cityscapes→Foggy Cityscapes | mAP@0.5:0.95: 23.8 -> 24.0 | Helped |
| Use single matching rather than multiple matching (ablation) | SIGMA matching · Cityscapes→Foggy Cityscapes | mAP@0.5: 43.1 -> 43.5 | Helped |
Closest papers by meaning
- CIGAR: Cross-Modality Graph Reasoning for Domain Adaptive Object Detection (CVPR 2023 · similarity 0.90)
- SEEN-DA: SEmantic ENtropy guided Domain-aware Attention for Domain Adaptive Object Detection (CVPR 2025 · similarity 0.89)
- Universal Domain Adaptive Object Detection via Dual Probabilistic Alignment (AAAI 2025 · similarity 0.89)
- DA-Ada: Learning Domain-Aware Adapter for Domain Adaptive Object Detection (NeurIPS 2024 · similarity 0.88)
- CAT: Exploiting Inter-Class Dynamics for Domain Adaptive Object Detection (CVPR 2024 · similarity 0.87)
- Large Self-Supervised Models Bridge the Gap in Domain Adaptive Object Detection (CVPR 2025 · similarity 0.87)
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