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Open access Aug 2026

Multi-level visual-language models feature learning for generalizable anomaly detection

A Multi-Level Feature Learning (MLFL) framework is proposed to enhance the zero-shot capability of CLIP via hierarchical alignment and introduces a Generalized Prompt Distillation (GPD) module that distills object-aware prompts into a unified representation.

Jianfeng Qiu, Junfa Li, Juan Xie et al. · 0 citations

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