Long Tail Learning With Class Descriptors

Long-tail learning through the utilization of category descriptors (such as attributes, category embeddings, etc.) aims to address the issue of uneven data distribution, improve the model's recognition ability for rare categories, and enhance overall generalization performance, which has significant application value.