uCAP: an unsupervised prompting method for vision-language models
This paper addresses a significant limitation that prevents Contrastive Language-Image Pretrained Models (CLIP) from achieving optimal performance on downstream image classification tasks. The key problem with CLIP-style zero-shot classification is that it requires domain-specific context in the for...
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| Materiálatiipa: | Conference item |
| Giella: | English |
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Springer
2024
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