Contextual Interaction via Primitive-based Adversarial Training For
Compositional Zero-shot Learning
Contextual Interaction via Primitive-based Adversarial Training For
Compositional Zero-shot Learning
Compositional Zero-shot Learning (CZSL) aims to identify novel compositions via known attribute-object pairs. The primary challenge in CZSL tasks lies in the significant discrepancies introduced by the complex interaction between the visual primitives of attribute and object, consequently decreasing the classification performance towards novel compositions. Previous remarkable works primarily addressed …