VISTA : A Visual Analytics Framework to Enhance Foundation Model-Generated Data Labels
The advances in multi-modal foundation models (FMs) (e.g., CLIP and LLaVA) have facilitated the auto-labeling of large-scale datasets, enhancing model performance in challenging downstream tasks such as open-vocabulary object detection and segmentation. However, the quality of FM-generated labels is...
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Détails bibliographiques
| Publié dans: | IEEE transactions on visualization and computer graphics. - 1996. - PP(2025) vom: 29. Jan.
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| Auteur principal: |
Xuan, Xiwei
(Auteur) |
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| Autres auteurs: |
Wang, Xiaoqi,
He, Wenbin,
Ono, Jorge Piazentin,
Gou, Liang,
Ma, Kwan-Liu,
Ren, Liu |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2025
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| Accès à la collection: | IEEE transactions on visualization and computer graphics
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| Sujets: | Journal Article |
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