Learning Pyramidal Feature Hierarchy for 3D reconstruction
| Language | English |
|---|---|
| Type | Letters |
| Authors | Fairuz Safwan Mahad, Masakazu Iwamura, Koichi Kise |
| Title | Learning Pyramidal Feature Hierarchy for 3D reconstruction |
| Journal | IEICE Transactions on Information and Systems |
| Vol. | E105-D |
| No. | 2 |
| Pages | pp.446-449 |
| Number of pages | 4 |
| Publisher | IEICE |
| Reviewed | Reviewed |
| Date | February 2022 |
| Research fields | 3D Reconstruction |
| DOI | 10.1587/transinf.2020ZDL0001 |
| Key | Mahad2022 (id=1850) |
Abstract
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.
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