Shape Completion Using 3D-Encoder-Predictor CNNs and Shape Synthesis
We introduce a data-driven approach to complete partial 3D shapes through a combination of volumetric deep neural networks and 3D shape synthesis. From a partially-scanned input shape, our method first infers a low-resolution - but complete - output. To this end, we introduce a 3D-Encoder-Predictor...
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| Published in: | 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) pp. 6545 - 6554 |
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| Main Authors: | , , |
| Format: | Conference Proceeding |
| Language: | English |
| Published: |
IEEE
01.07.2017
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| Subjects: | |
| ISSN: | 1063-6919, 1063-6919 |
| Online Access: | Get full text |
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