Papers › Cross-Domain Ensemble Distillation for Domain Generalization
Cross-Domain Ensemble Distillation for Domain Generalization
kyungmoon lee, Sungyeon Kim, Suha Kwak
Domain generalization is the task of learning models that generalize to unseen target domains. We propose a simple yet effective method for domain generalization, named cross-domain ensemble distillation (XDED), that learns domain-invariant features while encouraging the model to converge to flat minima, which recently turned out to be a sufficient condition for domain generalization. To this end, our method generates an ensemble of the output logits from training data with the same label but from different domains and then penalizes each output for the mismatch with the ensemble. Also, we present a de-stylization technique that standardizes features to encourage the model to produce style-consistent predictions even in an arbitrary target domain. Our method greatly improves generalization capability in public benchmarks for cross-domain image classification, cross-dataset person re-ID, and cross-dataset semantic segmentation. Moreover, we show that models learned by our method are robust against adversarial attacks and image corruptions.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Domain Generalization | Office-Home | XDED (ResNet-18) | Average Accuracy | 67.4 | #38 of 45 | Archive leaderboard | report |
| Domain Generalization | PACS | XDED (ResNet-18) | Average Accuracy | 86.4 | #48 of 133 | Archive leaderboard | report |
| Image to sketch recognition | PACS | XDED (ResNet18) | Accuracy | 51.5 | #5 of 7 | Archive leaderboard | report |
| Single-Source Domain Generalization | PACS | XDED (ResNet18) | Accuracy | 66.5 | #6 of 10 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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