3 papers
cs.CV2025
Bridge Feature Matching and Cross-Modal Alignment with Mutual-filtering for Zero-shot Anomaly Detection
Yuhu Bai, Jiangning Zhang, Yunkang Cao +4
With the advent of vision-language models (e.g., CLIP) in zero- and few-shot settings, CLIP has been widely applied to zero-shot anomaly detection (ZSAD) in recent research, where…
cs.CV2024
MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection
Haoyang He, Yuhu Bai, Jiangning Zhang +7
Recent advancements in anomaly detection have seen the efficacy of CNN- and transformer-based approaches. However, CNNs struggle with long-range dependencies, while transformers ar…
cs.CV2024
Dual-path Frequency Discriminators for Few-shot Anomaly Detection
Yuhu Bai, Jiangning Zhang, Zhaofeng Chen +3
Few-shot anomaly detection (FSAD) plays a crucial role in industrial manufacturing. However, existing FSAD methods encounter difficulties leveraging a limited number of normal samp…