Generating diverse augmented attributes for generalized zero shot learning.

•A generator is learned to augment semantic attributes to solve the projection problem of “many to one”.•The reconstructed features and the original features are concatenated to train the classifier.•The proposed method can achieve the SOTA performance on five datasets.