3DGS论文原理与论文源码学习，尽量无痛版

Core Insights - The article discusses the development and application of 3D Gaussian Splatting (3DGS) technology, emphasizing its significance in the field of autonomous driving and 3D reconstruction [3][9]. Group 1: Course Overview - The course titled "3DGS Theory and Algorithm Practical Tutorial" aims to provide a comprehensive learning roadmap for 3DGS, covering both theoretical and practical aspects [3][6]. - The course is designed for individuals interested in entering the 3DGS field, focusing on essential concepts such as point cloud processing and deep learning [3][6]. Group 2: Course Structure - Chapter 1 introduces foundational knowledge in computer graphics, including implicit and explicit representations of 3D space, rendering pipelines, and tools like SuperSplat and COLMAP [6][7]. - Chapter 2 delves into the principles and algorithms of 3DGS, covering dynamic reconstruction and surface reconstruction, with practical applications using the NVIDIA open-source 3DGRUT framework [7][8]. - Chapter 3 focuses on the application of 3DGS in autonomous driving simulations, highlighting key works and tools like DriveStudio for practical learning [8][9]. - Chapter 4 discusses important research directions in 3DGS, including COLMAP extensions and depth estimation, along with insights on their industrial and academic relevance [9][10]. - Chapter 5 covers Feed-Forward 3DGS, detailing its development and algorithmic principles, including recent works like AnySplat and WorldSplat [10]. - Chapter 6 provides a platform for Q&A and discussions on industry demands and challenges related to 3DGS [11]. Group 3: Target Audience and Requirements - The course is aimed at individuals with a background in computer graphics, visual reconstruction, and familiarity with technologies like NeRF and 3DGS [15]. - Participants are expected to have a basic understanding of probability theory, linear algebra, and proficiency in Python and PyTorch [15].