Fold is a post-hoc OOD detector that exploits larger feature-Hessian curvature on OOD inputs together with partial feature normalization and a self-supervised AutoFold calibration scheme.
In: ICCV (2025) 20 Park et al
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Exploiting Local Flatness for Efficient Out-of-Distribution Detection
Fold is a post-hoc OOD detector that exploits larger feature-Hessian curvature on OOD inputs together with partial feature normalization and a self-supervised AutoFold calibration scheme.