FINO adapts vision foundation models to scientific domains via metadata-guided self-supervised learning and outperforms both unsupervised domain adaptation and fully supervised methods without using task labels for the backbone.
Contrastive learning for fair representations.arXiv:2109.10645, 2021
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Who Needs Labels? Adapting Vision Foundation Models With the Metadata You Already Have
FINO adapts vision foundation models to scientific domains via metadata-guided self-supervised learning and outperforms both unsupervised domain adaptation and fully supervised methods without using task labels for the backbone.