What's the Situation with Intelligent Mesh Generation: A Survey and Perspectives

Intelligent mesh generation (IMG) refers to a technique for generating mesh by machine learning, which is a relatively new and promising research field. Within its short lifespan, IMG has greatly expanded the generalizability and practicality of mesh generation techniques, achieved many breakthroughs and created potential possibilities for mesh generation. However, there is a lack of surveys that focus on IMG methods in recent works. In this paper, we are committed to a systematic and comprehensive survey that describes the contemporary IMG landscape. Focusing on 113 preliminary IMG methods, we conducted an in-depth analysis from multiple perspectives, including the core technique and application scope of the algorithm, agent learning goals, data types, targeting challenges, advantages, and limitations. With the aim of literature collection and classification based on content extraction, we propose three different taxonomies from three views: key techniques, output mesh unit elements, and applicable input data types. We highlight some promising future research directions and challenges in IMG. To maximize the convenience of readers, a project page of IMG is provided at \url{https://github.com/xzb030/IMG_Survey}.