Revealing the Proximate Long-Tail Distribution in Compositional Zero-Shot Learning
Revealing the Proximate Long-Tail Distribution in Compositional Zero-Shot Learning
Compositional Zero-Shot Learning (CZSL) aims to transfer knowledge from seen state-object pairs to novel unseen pairs. In this process, visual bias caused by the diverse interrelationship of state-object combinations blurs their visual features, hindering the learning of distinguishable class prototypes. Prevailing methods concentrate on disentangling states and objects directly from …