Research map / Detection and segmentation / Open-set and few-shot detection
Strong-Weak Distribution Alignment for Adaptive Object Detection
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace strict cross-entropy global alignment with focal-loss weak global alignment | Faster R-CNN domain adaptation · Clipart | MAP: 25.6 to 36.4 | Helped |
| Add context-vector regularization (ablation) | Proposed weak global alignment · Clipart | MAP: 36.4 -> 37.5 | Helped |
| Add strong local alignment (ablation) | Proposed weak global alignment with context vector · Clipart | MAP: 37.5 -> 38.1 | Helped |
| Use global alignment with cross-entropy instead of weak global alignment | Faster R-CNN domain adaptation · PASCAL VOC source domain (adaptation to Clipart) | MAP: 77.5 -> 73.6 | Hurt |
| Add context-vector regularization (ablation) | Proposed weak global alignment · Watercolor | MAP: 49.8 -> 50.4 | Helped |
| Add strong local alignment (ablation) | Proposed weak global alignment with context vector · Watercolor | MAP: 50.4 -> 53.3 | Helped |
| Add strong local alignment to weak global alignment and context regularization (ablation) | Proposed detector adaptation · FoggyCityscapes | MAP: 29.5 -> 34.3 | Helped |
| Use strong local alignment without global alignment (ablation) | Proposed detector adaptation · FoggyCityscapes | MAP: 29.1 -> 27.9 | Hurt |
| Add context-vector regularization (ablation) | Proposed weak global alignment · FoggyCityscapes | MAP: 29.1 -> 29.5 | Helped |
| Replace weak global alignment with strict cross-entropy global alignment | Faster R-CNN domain adaptation · Cityscapes (Sim10k to Cityscapes, car) | AP: 31.8 -> 36.4 | Hurt |
| Set focal-loss gamma to 3 (ablation) | Proposed weak global alignment with context vector · Cityscapes (Sim10k to Cityscapes, car) | AP: 38.2 -> 42.3 | Helped |
| Use exponential focal loss instead of focal loss (ablation) | Proposed weak global alignment with context vector · Cityscapes (Sim10k to Cityscapes, car) | AP: 38.7 | Helped |
Closest papers by meaning
- Adapting Object Detectors via Selective Cross-Domain Alignment (CVPR 2019 · similarity 0.92)
- Improving Single Domain-Generalized Object Detection: A Focus on Diversification and Alignment (CVPR 2024 · similarity 0.89)
- Universal Domain Adaptive Object Detection via Dual Probabilistic Alignment (AAAI 2025 · similarity 0.88)
- Mean Teacher DETR with Masked Feature Alignment: A Robust Domain Adaptive Detection Transformer Framework (AAAI 2024 · similarity 0.87)
- Differential Alignment for Domain Adaptive Object Detection (AAAI 2025 · similarity 0.87)
- Unified Domain Generalization and Adaptation for Multi-View 3D Object Detection (NeurIPS 2024 · similarity 0.87)
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