Boosting Generative Zero-Shot Learning by Synthesizing Diverse Features with Attribute Augmentation
Boosting Generative Zero-Shot Learning by Synthesizing Diverse Features with Attribute Augmentation
The recent advance in deep generative models outlines a promising perspective in the realm of Zero-Shot Learning (ZSL). Most generative ZSL methods use category semantic attributes plus a Gaussian noise to generate visual features. After generating unseen samples, this family of approaches effectively transforms the ZSL problem into a supervised …