What's the Situation with Intelligent Mesh Generation: A Survey and
Perspectives
- URL: http://arxiv.org/abs/2211.06009v3
- Date: Tue, 23 May 2023 14:37:48 GMT
- Title: What's the Situation with Intelligent Mesh Generation: A Survey and
Perspectives
- Authors: Na Lei, Zezeng Li, Zebin Xu, Ying Li, and Xianfeng Gu
- Abstract summary: 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.
This paper endeavors to fill this gap by providing a systematic and thorough survey of the current IMG landscape.
- Score: 13.081274167488843
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: 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}.
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