Research map / Label-efficient and robust learning / Domain adaptation and generalization
MetaAlign: Coordinating Domain Alignment and Classification for Unsupervised Domain Adaptation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add MetaAlign to GVB | GVB · Office-Home | accuracy (Avg, %): 70.4 -> 71.3 | Helped |
| Add MetaAlign to DANNPE | DANNPE · Office-Home | accuracy (Avg, %): 68.3 -> 70.1 | Helped |
| Add MetaAlign to CDAN | CDAN · Office-Home | accuracy (Avg, %): 65.8 -> 67.8 | Helped |
| Add MetaAlign to DANN | DANN · Office-Home | accuracy (Avg, %): 59.2 -> 63.3 | Helped |
| Add MetaAlign to MMD | MMD · Office-Home | accuracy (Avg, %): 62.3 -> 63.3 | Helped |
| Add MetaAlign to GVB | GVB · Office31 | accuracy (Avg, %): 88.3 -> 89.2 | Helped |
| Add MetaAlign to DANNPE | DANNPE · PACS | accuracy (Avg., %): 80.7 -> 81.9; 1.2% | Helped |
| Add MetaAlign to SW-DA | SW-DA · Pascal VOC to Watercolor2k | mAP: 53.5 -> 55.6; 1.9 | Helped |
| Add MetaAlign to W-DA | W-DA · Pascal VOC to Watercolor2k | mAP: 49.8 -> 52.1; 2.3 | Helped |
| Remove learned layer-group weights β from MetaAlign (ablation) | DANNPE+MetaAlign · Office-Home | accuracy (Avg, %): 70.1 -> 69.7; 1.8%; 1.4% | Hurt |
| Exchange which task is meta-train and which is meta-test (ablation) | MetaAlign · UDA classification | accuracy: < 0.3% | No clear effect |
Closest papers by meaning
- ToAlign: Task-Oriented Alignment for Unsupervised Domain Adaptation (NeurIPS 2021 · similarity 0.91)
- Unsupervised Domain Adaptation Using Feature-Whitening and Consensus Loss (CVPR 2019 · similarity 0.90)
- CASUAL: Conditional Support Alignment for Domain Adaptation with Label Shift (AAAI 2025 · similarity 0.90)
- Enhancing Domain Adaptation through Prompt Gradient Alignment (NeurIPS 2024 · similarity 0.88)
- Universal Domain Adaptive Object Detection via Dual Probabilistic Alignment (AAAI 2025 · similarity 0.88)
- Prompt-Based Distribution Alignment for Unsupervised Domain Adaptation (AAAI 2024 · similarity 0.87)
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