Research map / Detection and segmentation / Open-set and few-shot detection
Task-Specific Inconsistency Alignment for Domain Adaptive Object Detection
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add task-specific inconsistency alignment for classification and localization | Faster R-CNN · PASCAL VOC → Clipart | mAP: 41.1 -> 46.3 | Helped |
| Add task-specific inconsistency alignment for classification and localization | Faster R-CNN · Cityscapes → Foggy Cityscapes | mAP: 39.2 -> 42.3 | Helped |
| Add task-specific inconsistency alignment | Faster R-CNN · KITTI → Cityscapes | car AP: 42.4 -> 44.0 | Helped |
| Add task-specific inconsistency alignment | Faster R-CNN · Cityscapes → KITTI | car AP: 73.0 -> 75.9 | Helped |
| Add classification-specific inconsistency alignment (ablation) | TIA · PASCAL VOC → Clipart | mAP: 41.1 -> 44.7 | Helped |
| Add localization-specific inconsistency alignment (ablation) | TIA · PASCAL VOC → Clipart | mAP: 41.1 -> 43.2 | Helped |
| Combine classification- and localization-specific alignment (ablation) | TIA · PASCAL VOC → Clipart | mAP: 44.7 -> 46.3; 43.2 -> 46.3 | Helped |
| Replace standard deviation with mean absolute deviation for localization disagreement (ablation) | TIA localization branch without classification alignment · PASCAL VOC → Clipart | mAP: 42.7 vs 43.2 | Hurt |
| Replace standard deviation with variance for localization disagreement (ablation) | TIA localization branch without classification alignment · PASCAL VOC → Clipart | mAP: 41.8 vs 43.2 | Hurt |
| Use L1 disagreement loss instead of the proposed inconsistency losses (ablation) | TIA · PASCAL VOC → Clipart | mAP | Hurt |
| Replace the proposed loss with KL divergence or SWD for predictor disagreement (ablation) | TIA · PASCAL VOC → Clipart | mAP | Hurt |
| Duplicate FCs and align their output features with DANN instead of task-specific inconsistency alignment (ablation) | Faster R-CNN · PASCAL VOC → Clipart | mAP | Hurt |
Closest papers by meaning
- Adapting Object Detectors via Selective Cross-Domain Alignment (CVPR 2019 · similarity 0.91)
- Universal Domain Adaptive Object Detection via Dual Probabilistic Alignment (AAAI 2025 · similarity 0.90)
- Improving Single Domain-Generalized Object Detection: A Focus on Diversification and Alignment (CVPR 2024 · similarity 0.90)
- Exploring Categorical Regularization for Domain Adaptive Object Detection (CVPR 2020 · similarity 0.89)
- RPN Prototype Alignment for Domain Adaptive Object Detector (CVPR 2021 · similarity 0.89)
- DSD-DA: Distillation-based Source Debiasing for Domain Adaptive Object Detection (ICML 2024 · similarity 0.88)
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