即将开课！做了一份3DGS的学习路线图，面向初学者......

Core Insights - The article emphasizes the rapid technological iteration in 3DGS (3D Graphics Systems), highlighting the transition from static reconstruction (3DGS) to dynamic reconstruction (4DGS) and surface reconstruction (2DGS) [1] - A new course titled "3DGS Theory and Algorithm Practical Tutorial" has been developed to provide a structured learning roadmap for individuals interested in entering the field, covering essential theories and practical coding skills [1] Course Overview - The course is designed to help newcomers understand the foundational concepts of computer graphics, including implicit and explicit representations of 3D space, rendering pipelines, ray tracing, and radiation field rendering [5] - It introduces commonly used development tools such as SuperSplat and COLMAP, along with the mainstream algorithm framework Gsplat [5] Chapter Summaries - Chapter 1: Background Knowledge This chapter provides an overview of 3DGS, starting with basic computer graphics concepts and tools necessary for model training [5] - Chapter 2: Principles and Algorithms Focuses on the core principles and pseudocode of 3DGS, covering dynamic reconstruction, surface reconstruction, and ray tracing, utilizing the NVIDIA open-source 3DGRUT framework for practical learning [6] - Chapter 3: Autonomous Driving 3DGS Concentrates on key works in the field, such as Street Gaussian and OmniRe, and uses DriveStudio for practical applications [7] - Chapter 4: Important Research Directions Discusses significant research areas in 3DGS, including COLMAP extensions and depth estimation, and their relevance to both industry and academia [8] - Chapter 5: Feed-Forward 3DGS Explores the rise of feed-forward 3DGS, detailing its development and algorithmic principles, along with recent works like AnySplat and WorldSplat [9] - Chapter 6: Q&A Discussion Organizes online discussions for participants to address industry needs, pain points, and open questions, facilitating deeper engagement with instructors [10] Target Audience and Learning Outcomes - The course is aimed at individuals with a foundational understanding of computer graphics, visual reconstruction, and programming in Python and PyTorch, who are looking to enhance their knowledge and skills in 3DGS [14] - Participants will gain comprehensive theoretical knowledge and practical experience in 3DGS algorithm development and frameworks, preparing them for various career opportunities in the field [14]