论文标题
智能网格生成的情况是什么：调查和观点
What's the Situation with Intelligent Mesh Generation: A Survey and Perspectives
论文作者
论文摘要
智能网格生成（IMG）代表了一个新颖而有希望的研究领域，利用机器学习技术来生成网格。尽管IMG相对起步，但IMG还是显着扩大了网格生成技术的适应性和实用性，带来了许多突破，并揭示了潜在的未来途径。但是，关于IMG方法的全面调查的当代文献中存在着一个明显的空白。本文通过对当前IMG景观进行系统的全面调查来填补这一空白。以113种初步的IMG方法的重点，我们从各个角度进行了细致的分析，包括核心算法技术及其应用程序范围，代理学习目标，数据类型，目标挑战以及优势和局限性。我们已经策划并分类了文献，提出了基于关键技术，输出网格单元元素和相关输入数据类型的三种独特分类法。本文还强调了IMG的几个有希望的未来研究方向和挑战。为了增强阅读器的可访问性，可以通过\ url {https://github.com/xzb030/img_survey}获得专用的IMG项目页面。
Intelligent Mesh Generation (IMG) represents a novel and promising field of research, utilizing machine learning techniques to generate meshes. Despite its relative infancy, IMG has significantly broadened the adaptability and practicality of mesh generation techniques, delivering numerous breakthroughs and unveiling potential future pathways. However, a noticeable void exists in the contemporary literature concerning comprehensive surveys of IMG methods. This paper endeavors to fill this gap by providing a systematic and thorough survey of the current IMG landscape. With a focus on 113 preliminary IMG methods, we undertake a meticulous analysis from various angles, encompassing core algorithm techniques and their application scope, agent learning objectives, data types, targeted challenges, as well as advantages and limitations. We have curated and categorized the literature, proposing three unique taxonomies based on key techniques, output mesh unit elements, and relevant input data types. This paper also underscores several promising future research directions and challenges in IMG. To augment reader accessibility, a dedicated IMG project page is available at \url{https://github.com/xzb030/IMG_Survey}.
