Dense 3D Object Reconstruction from a Single Depth View
In this paper, we propose a novel approach, 3D-RecGAN++, which reconstructs the complete 3D structure of a given object from a single arbitrary depth view using generative adversarial networks. Unlike existing work which typically requires multiple views of the same object or class labels to recover...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 41(2019), 12 vom: 05. Dez., Seite 2820-2834
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| 1. Verfasser: |
Yang, Bo
(VerfasserIn) |
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| Weitere Verfasser: |
Rosa, Stefano,
Markham, Andrew,
Trigoni, Niki,
Wen, Hongkai |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2019
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article |
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