Comparative Analysis of ControlGAN and ControlGAN-GP Models based Text-to-Image Synthesis

Abstract

This manuscript discuss the concept of Text-to-Image synthesis using machine learning methods. For machine learning purpose gradient adversarial network is used. Two different gradient adversarial network namely ControlGAN and ControlGAN-Gradient penalty method are used for the above mentioned task. The inclusion of Gradient-penalty in ControlGAN improves the convergence of the model which is evident from the performance matrices of the system. Microsoft COCO dataset is used for simulation and result validation purposes.