4 papers
CMDS-AD: Cross-Modal Dual-Stream Decoupling for Few-Shot Anomaly Detection
Junhao Cai, Junyu Chen, Deyu Zeng +4
Few-shot anomaly detection remains challenging due to limited training data. Multi-modal anomaly detection (MAD) offers a viable solution, leveraging 3D geometric cues to enrich 2D…
ForgeDreamer: Industrial Text-to-3D Generation with Multi-Expert LoRA and Cross-View Hypergraph
Junhao Cai, Deyu Zeng, Junhao Pang +3
Current text-to-3D generation methods excel in natural scenes but struggle with industrial applications due to two critical limitations: domain adaptation challenges where conventi…
Multimodal Task Representation Memory Bank vs. Catastrophic Forgetting in Anomaly Detection
You Zhou, Jiangshan Zhao, Deyu Zeng +3
Unsupervised Continuous Anomaly Detection (UCAD) faces significant challenges in multi-task representation learning, with existing methods suffering from incomplete representation…
A Survey on RGB, 3D, and Multimodal Approaches for Unsupervised Industrial Image Anomaly Detection
Yuxuan Lin, Yang Chang, Xuan Tong +8
In the advancement of industrial informatization, unsupervised anomaly detection technology effectively overcomes the scarcity of abnormal samples and significantly enhances the au…