Survey on 3D Scene Reconstruction Techniques in Metaverse

With the development of various technologies such as virtual reality(VR),augmented reality(AR),blockchain,and artificial intelligence(AI),the metaverse is gradually being applied in many fields such as gaming,education,healthcare,and business.As the core technology of the metaverse,3D reconstruction technology has attracted attention due to its extremely high research value and wide application prospects.Traditional 3D reconstruction techniques perform poorly in processing metaverse tasks characterized by real-time interactivity,with significant room for improvement in computational efficiency and reconstruction model accuracy.Therefore,how to optimize 3D reconstruction technology,improve accuracy and robustness,and provide users with a more realistic and real-time interactive experience has become a current research hotspot.This paper tracks and summarizes the 3D reconstruction techniques based on scene generation in the metaverse in recent years.Firstly,we review the deve-lopment history of the metaverse,point out the challenges faced by 3D reconstruction technology,and propose solutions based on two different 3D representations.Then,3D reconstruction techniques based on 3D Gaussian and Neural Radiance Field(NeRF) representations are sorted out separately.Next,the innovative fusion methods of 3D reconstruction technology with tactile signals and large language models are mainly analyzed.Finally,the challenges faced by scenebased 3D reconstruction technology in the metaverse are discussed in detail,and corresponding future research directions are proposed.