Advances in Image Generation Technology: Exploring GANs and MirrorGANs - Shi Lewuqiong (ITM Web of Conferences)
This paper is an in-depth study by delving into the latest in image generation technology, where thesis is focusing on the Generative Adversarial Networks (GANs) and MirrorGANs possibilities. Image Generation is the backbone of visual computing, mostly utilized in intelligent designs. It is for this reason that this research aims at unravelling the theoretical basis and consolidated practices of GANs when it conies to generating both high-quality and semantically consistent imagery. The study will investigate the whole of the image generation process, starting from data preprocessing to the use of GANs to generate images from textual descriptions. The work discussed the relevance as well as the limitations of these technologies from the artistic point of view, medical imaging, and virtual reality. Tire article concludes that the paper sketches the data and experiments that show that the realism and richness hi picture quality are accentuated when GANs and MirrorGANs are incorporated. This suggests the scope of image-generation technology to enhance human-machine collaboration and allow for innovating hi smart tech. Further studies will be geared to enhancing these methods and consequently drawing humanity and machines closer, which hi nun will fuel the ongoing progress in this fast-paced sphere.