2 papers
cs.CV2026
DPA: Decoupling Product-Agnostic Anomaly Representations for Zero-shot Anomaly Generation
Hang Yao, Yansheng Fu, Ming Liu +4
Industrial anomaly detection benefits from anomaly samples, yet newly deployed products typically provide only normal images, making anomaly samples difficult to collect. Zero-shot…
cs.LG2024
GTC: GNN-Transformer Co-contrastive Learning for Self-supervised Heterogeneous Graph Representation
Yundong Sun, Dongjie Zhu, Yansong Wang +1
Graph Neural Networks (GNNs) have emerged as the most powerful weapon for various graph tasks due to the message-passing mechanism's great local information aggregation ability. Ho…