activity
20242026
collaborators

14 papers

cs.CV2026

CoPS: Conditional Prompt Synthesis for Zero-Shot Anomaly Detection

Qiyu Chen, Zhen Qu, Wei Luo +7

Recently, large pre-trained vision-language models have shown remarkable performance in zero-shot anomaly detection (ZSAD). With fine-tuning on a single auxiliary dataset, the mode…

cs.CV2026

Template-Based Feature Aggregation Network for Industrial Anomaly Detection

Wei Luo, Haiming Yao, Wenyong Yu

Industrial anomaly detection plays a crucial role in ensuring product quality control. Therefore, proposing an effective anomaly detection model is of great significance. While exi…

cs.CV2026

A Feature Shuffling and Restoration Strategy for Universal Unsupervised Anomaly Detection

Wei Luo, Haiming Yao, Zhenfeng Qiang +2

Unsupervised anomaly detection is vital in industrial fields, with reconstruction-based methods favored for their simplicity and effectiveness. However, reconstruction methods ofte…

cs.CV2026

URA-Net: Uncertainty-Integrated Anomaly Perception and Restoration Attention Network for Unsupervised Anomaly Detection

Wei Luo, Peng Xing, Yunkang Cao +3

Unsupervised anomaly detection plays a pivotal role in industrial defect inspection and medical image analysis, with most methods relying on the reconstruction framework. However,…

cs.CV2025

Anomagic: Crossmodal Prompt-driven Zero-shot Anomaly Generation

Yuxin Jiang, Wei Luo, Hui Zhang +4

We propose Anomagic, a zero-shot anomaly generation method that produces semantically coherent anomalies without requiring any exemplar anomalies. By unifying both visual and textu…

cs.CV2025

A Comprehensive Survey for Real-World Industrial Defect Detection: Challenges, Approaches, and Prospects

Yuqi Cheng, Yunkang Cao, Haiming Yao +4

Industrial defect detection is vital for upholding product quality across contemporary manufacturing systems. As the expectations for precision, automation, and scalability intensi…