Towards Real-time 3D Computer-Generated Holography with Inverse Neural Network for Near-eye Displays

Abstract

Holography plays a vital role in the advancement of virtual reality (VR) and augmented reality (AR) display technologies. Its ability to create realistic three-dimensional (3D) imagery is crucial for providing immersive experiences to users. However, existing computer-generated holography (CGH) algorithms used in these technologies are either slow or not 3D-compatible. This article explores four inverse neural network architectures to overcome these issues for real time and 3D applications.