CLIP-driven Outliers Synthesis for few-shot OOD detection
CLIP-driven Outliers Synthesis for few-shot OOD detection
Few-shot OOD detection focuses on recognizing out-of-distribution (OOD) images that belong to classes unseen during training, with the use of only a small number of labeled in-distribution (ID) images. Up to now, a mainstream strategy is based on large-scale vision-language models, such as CLIP. However, these methods overlook a crucial …