Zero-Shot Learning (ZSL) aims to generalize a pretrained classification model to unseen classes with the help of auxiliary semantic information. Recent generative methods are based on the paradigm of synthesizing unseen visual data from class attributes. A mapping is learnt from semantic attributes to visual features extracted by a pre-trained backbone such as ResNet101 by training a generative adversarial network. Considering the domain-shift problem between pre-trained backbone and task ZSL dataset as well as th…