A zero-shot learning framework via cluster-prototype matching

•A novel Cluster-Prototype Matching (CPM) strategy is proposed to solve the domain shift problem of zero-shot learning.•The distribution information of samples in the embedding space, i.e., cluster structure, is utilized to assist in zero-shot learning classification.•The CPM strategy can be applied to most existing ZSL models in a plug-and-play style.•Extensive experiments show the effectiveness and robustness of the proposed method.