A Survey in Virtual Image Generation Based on Generative Adversarial Networks

With the rapid development of the metaverse, this is the inevitable trend content form from 2D to 3D, from real to virtual to virtual-real combination. The demand for virtual scenes will surge in the coming period. How to quickly generate a large number of high-quality scene graphs has sparked extensive academic attention. GAN being the most popular generation algorithm, and we discuss the prevalent architectures to solve the problems of training collapse and uncontrollable images during training. Besides, this paper focuses on the development of GAN and its variants in the field of image synthesis. A comprehensive review of recent advances in virtual image generation in the last two years is presented, with a summary of the classification of algorithms and an introduction to techniques related to multimodal generation. Finally, some suggestions for future research directions are proposed.