Scene reconstruction techniques for autonomous driving: a review of 3D Gaussian splatting

Abstract

As the latest research result of the explicit radiated field technology, 3D Gaussian Splatting (3D GS) replaces the implicit expression represented by Neural Radiated Field (NeRF) and has become the hottest research direction in 3D scene reconstruction. Given the innovative work and vigorous development of 3D GS in autonomous driving, this paper comprehensively reviews and summarizes the existing related research to showcase the evolution of the 3D GS technology and possible future development directions. First, the overall research background of 3D GS is introduced based on two aspects 3D scene reconstruction methods and 3D GS research progress. Second, the relevant knowledge points of 3D GS and the core formulas to clarify the mathematical mechanism of 3D GS are presented. Third, the primary applications of the 3D scene reconstruction technology based on 3D GS in automatic driving are presented through new perspective synthesis, scene understanding, and simultaneous localization and map building (SLAM). Finally, the research frontier directions of 3D GS in autonomous driving are described, including structure optimization, 4D scene reconstruction, and cross-domain research. This paper may provide an effective and convenient pathway for researchers to understand, explore, apply this novel research method, and promote the development and application of 3D GS in automatic driving.