HDM: Heat Diffusion Mesh for Mesh Representation
Authors: 
Tingting Li, Yunhui Shi, Jin WangAuthors Info & Claims
Tingting Li, Yunhui Shi, Jin WangAuthors Info & ClaimsPages 202 - 206
Abstract
The applications of 3D mesh, such as computer vision, molecular biology, and medical imaging, have received sufficient attention recently. Polygonal meshes are a significant raw representation of 3D shapes thanks to their compactness and flexibility. Though extensive research efforts are concentrating on how to represent 3D shapes well based on voxels and point clouds, there is little effort on meshes due to their irregularity. To tackle the challenge, we propose a new mesh representation called Heat Diffusion Mesh (HDM) in this paper. It represents meshes that are in non-Euclidean domains as a space-time signal by heat diffusion. Experiments of mesh classification and segmentation show the effectiveness of the proposed mesh representation.
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Index Terms
- HDM: Heat Diffusion Mesh for Mesh Representation
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Published In
December 2022
406 pages
ISBN:9781450399067
DOI:10.1145/3578741
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Published: 06 March 2023
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MLNLP 2022
MLNLP 2022: 2022 5th International Conference on Machine Learning and Natural Language Processing
December 23 - 25, 2022
Sanya, China
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