Xiaokun Li

CLIP-driven Coarse-to-fine Semantic Guidance for Fine-grained Open-set Semi-supervised Learning

Fine-grained open-set semi-supervised learning (OSSL) investigates a practical scenario where unlabeled data may contain fine-grained out-of-distribution (OOD) samples. Due to the subtle visual differences among in-distribution (ID) samples, as well as between ID and OOD samples, it is extremely cha…