Multi-view Fusion 3D Model Classification
At present, view-based 3D model classification is a research hotspot. However, current methods produce many redundant views, and all views are treated equally, ignoring their differences and importance. To solve the above problems, we propose a multi-view fusion 3D model classification method. This...
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| Format: | Article |
| Language: | zho |
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Harbin University of Science and Technology Publications
2022-06-01
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| Series: | Journal of Harbin University of Science and Technology |
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| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2096 |
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| author | GAO Yuan DING Bo HE Yong-jun |
| author_facet | GAO Yuan DING Bo HE Yong-jun |
| author_sort | GAO Yuan |
| collection | DOAJ |
| description | At present, view-based 3D model classification is a research hotspot. However, current methods produce many redundant views, and all views are treated equally, ignoring their differences and importance. To solve the above problems, we propose a multi-view fusion 3D model classification method. This method first extracts view features using the view feature extraction network with mixed domain attention, and then fuses these view features and inputs the fused features into the view weight learning network with channel attention, giving different weights to different views according to their importance to the 3D model, and forming representative feature descriptors for 3D model classification. Experimental results shows that the classification accuracy rates in the rigid 3D model data sets ModelNet10 and ModelNet40 reached 98.3% and 95.5%. |
| format | Article |
| id | doaj-art-ea73bff5cd144e1db0eda62cb59ea8ec |
| institution | DOAJ |
| issn | 1007-2683 |
| language | zho |
| publishDate | 2022-06-01 |
| publisher | Harbin University of Science and Technology Publications |
| record_format | Article |
| series | Journal of Harbin University of Science and Technology |
| spelling | doaj-art-ea73bff5cd144e1db0eda62cb59ea8ec2025-08-20T02:48:06ZzhoHarbin University of Science and Technology PublicationsJournal of Harbin University of Science and Technology1007-26832022-06-012703596510.15938/j.jhust.2022.03.008Multi-view Fusion 3D Model ClassificationGAO Yuan0DING Bo1HE Yong-jun2School of Computer Science and Technology, Harbin University of Science and Technology Harbin 150080School of Computer Science and Technology, Harbin University of Science and Technology Harbin 150080School of Computer Science and Technology, Harbin University of Science and Technology Harbin 150080At present, view-based 3D model classification is a research hotspot. However, current methods produce many redundant views, and all views are treated equally, ignoring their differences and importance. To solve the above problems, we propose a multi-view fusion 3D model classification method. This method first extracts view features using the view feature extraction network with mixed domain attention, and then fuses these view features and inputs the fused features into the view weight learning network with channel attention, giving different weights to different views according to their importance to the 3D model, and forming representative feature descriptors for 3D model classification. Experimental results shows that the classification accuracy rates in the rigid 3D model data sets ModelNet10 and ModelNet40 reached 98.3% and 95.5%.https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=20963d model classificationconvolution neural networkattention mechanismfeature fusion |
| spellingShingle | GAO Yuan DING Bo HE Yong-jun Multi-view Fusion 3D Model Classification Journal of Harbin University of Science and Technology 3d model classification convolution neural network attention mechanism feature fusion |
| title | Multi-view Fusion 3D Model Classification |
| title_full | Multi-view Fusion 3D Model Classification |
| title_fullStr | Multi-view Fusion 3D Model Classification |
| title_full_unstemmed | Multi-view Fusion 3D Model Classification |
| title_short | Multi-view Fusion 3D Model Classification |
| title_sort | multi view fusion 3d model classification |
| topic | 3d model classification convolution neural network attention mechanism feature fusion |
| url | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2096 |
| work_keys_str_mv | AT gaoyuan multiviewfusion3dmodelclassification AT dingbo multiviewfusion3dmodelclassification AT heyongjun multiviewfusion3dmodelclassification |