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Recent advances in 3D Gaussian splatting

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摘要 The emergence of 3D Gaussian splatting(3DGS)has greatly accelerated rendering in novel view synthesis.Unlike neural implicit representations like neural radiance fields(NeRFs)that represent a 3D scene with position and viewpoint-conditioned neural networks,3D Gaussian splatting utilizes a set of Gaussian ellipsoids to model the scene so that efficient rendering can be accomplished by rasterizing Gaussian ellipsoids into images.Apart from fast rendering,the explicit representation of 3D Gaussian splatting also facilitates downstream tasks like dynamic reconstruction,geometry editing,and physical simulation.Considering the rapid changes and growing number of works in this field,we present a literature review of recent 3D Gaussian splatting methods,which can be roughly classified by functionality into 3D reconstruction,3D editing,and other downstream applications.Traditional point-based rendering methods and the rendering formulation of 3D Gaussian splatting are also covered to aid understanding of this technique.This survey aims to help beginners to quickly get started in this field and to provide experienced researchers with a comprehensive overview,aiming to stimulate future development of the 3D Gaussian splatting representation.
出处 《Computational Visual Media》 SCIE EI CSCD 2024年第4期613-642,共30页 计算可视媒体(英文版)
基金 supported by the National Natural Science Foundation of China(62322210) Beijing Municipal Natural Science Foundation for Distinguished Young Scholars(JQ21013) Beijing Municipal Science and Technology Commission(Z231100005923031) 2023 Tencent AI Lab Rhino-Bird Focused Research Program.

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