An Efficient Appraoch based Representation Learning and CRF Models for Unsupervised 3D Shape Co-segmentation-Reference-Cited by-同舟云学术

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An Efficient Appraoch based Representation Learning and CRF Models for Unsupervised 3D Shape Co-segmentation

Published:2023-12-16 Issue: Volume: Page:245-250
ISSN:
Container-title:2023 7th IEEE Congress on Information Science and Technology (CiSt)
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Author:

Abouqora Youness¹,Benhaila Zakaria¹,Moumoun Lahcen²

Affiliation:

1. Hassan 1st University,Laboratory of Mathematics, Computer Science and Engineering Sciences Faculty of Sciences and Techniques,Settat,Morocco

2. Hassan 1st University,Laboratory of Mathematics, Computer Science and Engineering Sciences,Department of Computer Engineering and Mathematics,Settat,Morocco

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10409867/10409868/10409928.pdf?arnumber=10409928

Reference36 articles.

1. Consistent segmentation of 3D models

2. Interactive shape co-segmentation via label propagation

3. Unsupervised co-segmentation of a set of shapes via descriptor-space spectral clustering

4. Unsupervised co-segmentation of 3D shapes via affinity aggregation spectral clustering

5. Co-Segmentation of 3D Shapes via Subspace Clustering

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