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...
| Main Authors: | , , , , |
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| 格式: | Journal article |
| 出版: |
Institute of Electrical and Electronics Engineers
2018
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