Research map / Label-efficient and robust learning / Domain adaptation and generalization
Domain Generalization via Model-Agnostic Learning of Semantic Features
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| MASF (episodic training + global alignment + local clustering) | DeepAll AlexNet · PACS | average accuracy: 71.70 -> 75.21 | Helped |
| MASF | DeepAll · VLCS | average accuracy: 72.19 -> 74.11 | Helped |
| add episodic meta-learning to global+local losses (ablation) | MASF · PACS | average accuracy: 73.88 -> 75.21 | Helped |
| add global class alignment loss (ablation) | MASF (episodic + local) · PACS | average accuracy: 74.02 -> 75.21 | Helped |
| add local sample clustering loss (ablation) | MASF (episodic + global) · PACS | average accuracy: 73.93 -> 75.21 | Helped |
| episodic training alone (MLDG-like) (ablation) | DeepAll · PACS Sketch | accuracy: 61.13 -> 59.89 | Hurt |
| episodic training alone (ablation) | DeepAll · PACS | average accuracy: 71.70 -> 72.52 | Helped |
| MASF with deeper backbone | DeepAll ResNet-50 · PACS Photo | accuracy: 94.83 -> 95.01 | No clear effect |
| MASF | DeepAll U-Net · Brain MRI Set-B | Dice: 90.41 -> 91.71 | Helped |
| apply metric regularization directly on features instead of via embedding network (ablation) | MASF · unseen domains | generalization | Hurt |
| JS divergence instead of symmetrized KL (ablation) | global alignment loss · preliminary experiments | accuracy | No clear effect |
Closest papers by meaning
- Open Domain Generalization with Domain-Augmented Meta-Learning (CVPR 2021 · similarity 0.91)
- DIRL: Domain-Invariant Representation Learning for Generalizable Semantic Segmentation (AAAI 2022 · similarity 0.90)
- Towards Generalizing to Unseen Domains with Few Labels (CVPR 2024 · similarity 0.88)
- SoMA: Singular Value Decomposed Minor Components Adaptation for Domain Generalizable Representation Learning (CVPR 2025 · similarity 0.88)
- CLIPCEIL: Domain Generalization through CLIP via Channel rEfinement and Image-text aLignment (NeurIPS 2024 · similarity 0.88)
- Gradient-Guided Annealing for Domain Generalization (CVPR 2025 · similarity 0.88)
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