2 papers
cs.CV2026
Hyper-FSAD: Training-Free and Language-Free Few-Shot Anomaly Detection via Sparse Hyper Matching
Guohuan Xie, Xin He, Dingying Fan +2
Few-shot anomaly detection (FSAD) is particularly valuable when only a few normal images are available in a new target domain, while anomalous cases are rare, diverse, and difficul…
cs.CV2026
Make It Up: Fake Images, Real Gains in Generalized Few-shot Semantic Segmentation
Guohuan Xie, Xin He, Dingying Fan +3
Generalized few-shot semantic segmentation (GFSS) is fundamentally limited by the coverage of novel-class appearances under scarce annotations. While diffusion models can synthesiz…