当我们把3DGS在工业界的应用展开后......

Core Viewpoint - The article discusses the advancements and applications of 3D Generative Systems (3DGS) in the context of autonomous driving, emphasizing the importance of scene reconstruction and generation technologies for creating realistic driving environments [1][3]. Group 1: Scene Reconstruction Work - The publication of StreetGaussian at ECCV2024 marks a significant step in the wave of autonomous driving scene reconstruction [2]. - A large-scale vehicle asset reconstruction dataset named 3DRealCar has been released [2]. - The Balanced3DGS algorithm accelerates 3DGS training by nearly eight times [2]. - The Hierarchy UGP paper is set to be presented at ICCV2025, focusing on autonomous driving scene reconstruction [2]. - StyledStreets introduces a multi-style scene generation algorithm with spatiotemporal consistency for autonomous driving [2]. Group 2: Importance of Scene Reconstruction - Traditional vehicle testing heavily relies on real-world tests, which often fail to replicate many corner cases, and there is a significant domain gap in conventional simulation environments [3]. - The high-fidelity scene reconstruction and editing capabilities of 3DGS make it possible to address these challenges [3]. - The development trajectory of 3DGS is clear: static reconstruction → dynamic reconstruction → hybrid reconstruction → feed-forward GS, with applications extending beyond autonomous driving to 3D fields, embodied intelligence, and the gaming industry [3]. Group 3: 3DGS Learning Path - A comprehensive learning roadmap for 3DGS has been developed, covering point cloud processing, deep learning theories, real-time rendering, and practical coding [5]. - The course titled "3DGS Theory and Algorithm Practical Tutorial" aims to provide a structured approach to mastering the 3DGS technology stack [5]. Group 4: Course Structure - The course consists of six chapters, starting with foundational knowledge in computer graphics and progressing through principles, algorithms, and specific applications in autonomous driving [10][11][12][13][14]. - Each chapter includes practical assignments and discussions on important research directions and industry applications [13][14][15]. Group 5: Target Audience and Outcomes - The course is designed for individuals with a background in computer graphics, visual reconstruction, and programming, aiming to equip them with comprehensive knowledge and skills in 3DGS [19]. - Participants will gain insights into industry demands, pain points, and opportunities for further engagement with academic and industrial peers [15][19].