Learning Domain Invariant Prompt for Vision-Language Models
Prompt learning stands out as one of the most efficient approaches for adapting powerful vision-language foundational models like CLIP to downstream datasets by tuning learnable prompt vectors with very few samples. However, despite its success in achieving remarkable performance on in-domain data,...
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Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 33(2024) vom: 09., Seite 1348-1360
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| 1. Verfasser: |
Zhao, Cairong
(VerfasserIn) |
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| Weitere Verfasser: |
Wang, Yubin,
Jiang, Xinyang,
Shen, Yifei,
Song, Kaitao,
Li, Dongsheng,
Miao, Duoqian |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2024
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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| Schlagworte: | Journal Article |
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