SCMS-Net: Self-Supervised Clustering-Based 3D Meshes Segmentation Network-Reference-Cited by-同舟云学术

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SCMS-Net: Self-Supervised Clustering-Based 3D Meshes Segmentation Network

Published:2023-07 Issue: Volume:160 Page:103512
ISSN:0010-4485
Container-title:Computer-Aided Design
language:en
Short-container-title:Computer-Aided Design

Author:

Jiao Xue^ORCID,Chen Yonggang,Yang Xiaohui

Funder

Henan Province Natural Science Foundation

Key Scientific Research Project of Colleges and Universities in Henan Province

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Computer Graphics and Computer-Aided Design,Computer Science Applications

Reference58 articles.

1. StructureNet;Mo;ACM Trans Graph,2019

2. Wang L, Li X, Fang Y. Few-Shot Learning of Part-Specific Probability Space for 3D Shape Segmentation. In: 2020 IEEE/CVF conference on computer vision and pattern recognition. 2020, p. 4503–12.

3. Yi L, Su H, Guo X, Guibas L. SyncSpecCNN: Synchronized Spectral CNN for 3D Shape Segmentation. In: 2017 IEEE conference on computer vision and pattern recognition. 2017, p. 6584–92.

4. Part-based mesh segmentation: A survey;Rodrigues;Comput Graph Forum,2018

5. A survey on mesh segmentation techniques;Shamir;Comput Graph Forum,2008

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1. An overview on deep clustering;Neurocomputing;2024-07

2. Applications of Convolutional Neural Networks to Extracting Oracle Bone Inscriptions from Three-Dimensional Models;Symmetry;2023-08-12

3. A data-centric unsupervised 3D mesh segmentation method;The Visual Computer;2023-06-13

4. Supervertex Sampling Network: A Geodesic Differential SLIC Approach for 3D Mesh;IEEE Transactions on Visualization and Computer Graphics;2023

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