最近Feed-forward GS的工作爆发了

Core Viewpoint - The article discusses the advancements in 3D Gaussian Splatting (3DGS) technology in the autonomous driving sector, highlighting the introduction of feed-forward GS algorithms and the need for effective learning pathways for newcomers in the field [2][4]. Group 1: Course Overview - A new course titled "3DGS Theory and Algorithm Practical Tutorial" has been developed to provide a comprehensive learning roadmap for 3DGS technology, covering both theoretical and practical aspects [4]. - The course is designed to help participants understand point cloud processing, deep learning theories, real-time rendering, and coding practices [4]. Group 2: Course Structure - The course consists of six chapters, starting with foundational knowledge in computer graphics and moving through the principles and algorithms of 3DGS, including dynamic and surface reconstruction [8][9]. - The third chapter focuses on the application of 3DGS in autonomous driving simulation, providing insights into key works and tools used in the industry [10]. - Subsequent chapters explore important research directions in 3DGS, including COLMAP extensions and depth estimation, as well as the emerging feed-forward 3DGS techniques [11][12]. Group 3: Target Audience and Requirements - The course is aimed at individuals with a background in computer graphics, visual reconstruction, and programming, specifically those familiar with Python and PyTorch [17]. - Participants are expected to have access to a GPU with a recommended capability of 4090 or higher to effectively engage with the course content [17].