Research map / Label-efficient and robust learning / Domain adaptation and generalization
Unsupervised Domain Adaptation With Hierarchical Gradient Synchronization
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add class-wise alignment to global alignment (ablation) | GSDA · Office-31-DA | accuracy: 83.7 -> 85.6 | Helped |
| Add group-wise alignment to global and class-wise alignment (ablation) | GSDA · Office-31-DA | accuracy: 85.6 -> 87.0 | Helped |
| Add hierarchical gradient synchronization to global, class-wise, and group-wise alignment (ablation) | GSDA · Office-31-DA | accuracy: 87.0 -> 89.7 | Helped |
Closest papers by meaning
- Exploiting Local Feature Patterns for Unsupervised Domain Adaptation (AAAI 2019 · similarity 0.92)
- Structure-Aware Feature Fusion for Unsupervised Domain Adaptation (AAAI 2020 · similarity 0.90)
- Co-regularized Alignment for Unsupervised Domain Adaptation (NeurIPS 2018 · similarity 0.89)
- Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation (AAAI 2019 · similarity 0.89)
- Unsupervised Domain Adaptation Using Feature-Whitening and Consensus Loss (CVPR 2019 · similarity 0.89)
- ToAlign: Task-Oriented Alignment for Unsupervised Domain Adaptation (NeurIPS 2021 · similarity 0.89)
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