DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-To-Image Synthesis

In this paper, we focus on generating realistic images from text descriptions. Current methods first generate an initial image with rough shape and color, and then refine the initial image to a high-resolution one. Most existing text-to-image synthesis methods have two main problems. (1) These methods depend heavily on the quality of the initial images. If the initial image is not well initialized, the following processes can hardly refine the image to a satisfactory quality. (2) Each word contributes a different level of importance when depicting different image contents, however, unchanged text representation is used in existing image refinement processes. In this paper, we propose the Dynamic Memory…

• NN
  National Natural Science Foundation of China

  Awards: U1866602, 61772456
• NK
  National Key Research and Development Program of China

  Award: 2018YFB0904503