Research Progress of Semantic Image Synthesis

Semantic image synthesis is a cutting-edge technique that employs semantic labels to generate realistic images. This technique has gained widespread popularity in the field of image synthesis, and has become a powerful tool for producing diverse and creative images. With the continued advancement of deep generation models, more sophisticated techniques are being developed for semantic image synthesis. In this paper, we introduce the fundamental concepts underlying diffusion-based and adversarial generative networks-based semantic image synthesis techniques. Additionally, we analyze the distinctive features of various models, propose two visualization schemes for generative models, and address the issue of pattern-running. Finally, we provide a summary and future outlook on the challenges and development trends of deep generative models, offering valuable insights for both researchers and practitioners.