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…
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…
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…