Realistic image generation in virtual reality using deep learning techniques

Abstract

This article introduces the widespread application of DL (Deep Learning) technology in VR (Virtual Reality), and then points out the challenges that exist in virtual environments and virtual character image generation tasks, such as the complexity of factors such as lighting, materials, textures, expressions, and actions. Furthermore, the main objective of this study was clarified, which is to achieve realistic virtual image generation through DL technology. The research questions include how to improve the realism and realism of virtual environments, as well as how to achieve realistic expression and action generation of virtual characters. These issues highlight the importance and potential applications of research. Subsequently, a brief introduction was given to the research methods, particularly the use of autoencoder models to learn potential representations of virtual environments and virtual characters, in order to achieve realistic image generation. The selection of these models highlights the crucial role of DL technology in image generation tasks.