Learning Pyramidal Feature Hierarchy for 3D Reconstruction
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- MAHAD Fairuz Safwan
- Dept. of Computer Science and Intelligent Systems, Graduate School of Engineering, Osaka Prefecture University
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- IWAMURA Masakazu
- Dept. of Computer Science and Intelligent Systems, Graduate School of Engineering, Osaka Prefecture University
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- KISE Koichi
- Dept. of Computer Science and Intelligent Systems, Graduate School of Engineering, Osaka Prefecture University
Abstract
<p>Neural network-based three-dimensional (3D) reconstruction methods have produced promising results. However, they do not pay particular attention to reconstructing detailed parts of objects. This occurs because the network is not designed to capture the fine details of objects. In this paper, we propose a network designed to capture both the coarse and fine details of objects to improve the reconstruction of the fine parts of objects.</p>
Journal
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- IEICE Transactions on Information and Systems
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IEICE Transactions on Information and Systems E105.D (2), 446-449, 2022-02-01
The Institute of Electronics, Information and Communication Engineers
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Details
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- CRID
- 1390853879728077056
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- NII Article ID
- 130008149850
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- ISSN
- 17451361
- 09168532
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- Text Lang
- en
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed