Three‐dimensional shape reconstruction of objects from a single depth view using deep U‐Net convolutional neural network with bottle‐neck skip connections
Abstract Three‐dimensional (3D) shape reconstruction of objects requires multiple scans and complex reconstruction algorithms. An alternative approach is to infer the 3D shape of an object from a single depth image (i.e. single depth view). This study presents such a 3D shape reconstructor based on...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-02-01
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| Series: | IET Computer Vision |
| Online Access: | https://doi.org/10.1049/cvi2.12014 |