Too Long; Didn't Read
This blog addresses different text to image synthesis algorithms using GAN (Generative Adversarial Network) that aims to directly map words and characters to image pixels with natural language representation and image synthesis techniques. The featured algorithms learn a text feature representation that captures the important visual details and then use these features to synthesize a compelling image that a human might mistake for real. The author concludes that the best thing is to combine the generality of text descriptions with the discriminative power of attributes.