Han ye

Leaving No OOD Instance Behind: Instance-Level OOD Fine-Tuning for Anomaly Segmentation

Out-of-distribution (OOD) fine-tuning has emerged as a promising approach for anomaly segmentation. Current OOD fine-tuning strategies typically employ global-level objectives, aiming to guide segmentation models to accurately predict a large number of anomaly pixels. However, these strategies often…