Rethinking Zero-Shot Learning: A Conditional Visual Classification Perspective
Rethinking Zero-Shot Learning: A Conditional Visual Classification Perspective
Zero-shot learning (ZSL) aims to recognize instances of unseen classes solely based on the semantic descriptions of the classes. Existing algorithms usually formulate it as a semantic-visual correspondence problem, by learning mappings from one feature space to the other. Despite being reasonable, previous approaches essentially discard the highly precious discriminative …