Poster "multi-class anomaly detection" Papers

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Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection

Jia Guo, Shuai Lu, Weihang Zhang et al.

CVPR 2025arXiv:2405.14325

Continuous Memory Representation for Anomaly Detection

Joo Chan Lee, Taejune Kim, Eunbyung Park et al.

ECCV 2024arXiv:2402.18293

Learning to Detect Multi-class Anomalies with Just One Normal Image Prompt

Bin-Bin Gao

ECCV 2024arXiv:2505.09264

Learning Unified Reference Representation for Unsupervised Multi-class Anomaly Detection

Liren He, Zhengkai Jiang, Jinlong Peng et al.

ECCV 2024arXiv:2403.11561

Vague Prototype-Oriented Diffusion Model for Multi-Class Anomaly Detection

yuxin li, Yaoxuan Feng, Bo Chen et al.