Consistent Augmentation Learning for Generalizing CLIP to Unseen Domains
Domain generalization (DG) is a challenging transfer learning task focused on learning invariant knowledge from limited source domains, thereby enhancing generalization to the out-of-distribution data in unseen domains. Recent advancements in vision-language models (VLMs) have notably boosted the ca...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10716475/ |
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