Text to Image Generation

  • Unique Paper ID: 159511
  • Volume: 9
  • Issue: 12
  • PageNo: 1065-1069
  • Abstract:
  • Machine Learning enables near-perfect algorithmic compositions. The proposed solution, Stacked Generative Adversarial Networks, generates photo-realistic images from text descriptions by decomposing the problem into manageable sub-problems through a sketch-refinement process. The Stage-I GAN sketches low-resolution images of the object's primitive shape and colors. The Stage-II GAN generates high-resolution images with photo-realistic details by rectifying defects in Stage-I results and adding compelling details with the refinement process. A Conditioning Augmentation technique improves diversity and stabilizes training. The proposed method achieves significant improvements in generating photo-realistic images conditioned on text descriptions.

Cite This Article

  • ISSN: 2349-6002
  • Volume: 9
  • Issue: 12
  • PageNo: 1065-1069

Text to Image Generation

Related Articles