A continual few-shot adaptation method combining binary cross-entropy and supervised contrastive losses with replay achieves a good trade-off between fast adaptation to unseen synthetic fingerprint styles and retention of known styles.
Learning transferable visual models from natural language supervision,
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Continual Few-shot Adaptation for Synthetic Fingerprint Detection
A continual few-shot adaptation method combining binary cross-entropy and supervised contrastive losses with replay achieves a good trade-off between fast adaptation to unseen synthetic fingerprint styles and retention of known styles.