activity
20222025
most citedPracticalDG: Perturbation Distillation on Vision-Language Models for Hybrid Domain Generalization

1 citations · 1 across the 4 of their papers we have counts for

collaborators
Showing 2024Show all

2 papers · 1 filter

cs.CV2024

Filter or Compensate: Towards Invariant Representation from Distribution Shift for Anomaly Detection

Zining Chen, Xingshuang Luo, Weiqiu Wang +3

Recent Anomaly Detection (AD) methods have achieved great success with In-Distribution (ID) data. However, real-world data often exhibits distribution shift, causing huge performan…

cs.CV2024★ 1 cited

PracticalDG: Perturbation Distillation on Vision-Language Models for Hybrid Domain Generalization

Zining Chen, Weiqiu Wang, Zhicheng Zhao +3

Domain Generalization (DG) aims to resolve distribution shifts between source and target domains, and current DG methods are default to the setting that data from source and target…