FINO

FINO: Label-free adaptation of vision foundation models using metadata in scientific domains

Researchers propose FINO, a self-supervised method for adapting vision foundation models to specialized scientific domains without task labels, using metadata as a guidance signal instead. The approach combines a standard self-supervised objective with flexible handling of both discrete and continuous metadata to preserve informative factors while suppressing spurious ones. Evaluated across subcellular fluorescence microscopy, Earth observation, wildlife monitoring, and medical imaging, FINO outperforms both unsupervised domain adaptation and fully supervised fine-tuning, including domain-specific state-of-the-art models.