Comparative Study of Different Adversarial Text to Image Methods Introduction Automatic synthesis of realistic images from text has become popular with deep convolutional and recurrent neural network architectures to aid in learning discriminative text feature representations. Discriminative power and strong generalization properties of attribute representations even though attractive, its a complex process and requires domain-specific knowledge. Over the years the techniques have evolved as auto-adversarial networks in space of machine learning algorithms continue to evolve. In comparison, natural language offers an easy, general, and flexible plugin that can be used to […]
