SELF-SUPERVISED ADVERSARIAL SHAPE COMPLETION
The goal of this paper is 3D shape completion: given an incomplete instance of a known category, hallucinate a complete version of it that is geometrically plausible. We develop an adversarial framework that makes it possible to learn shape completion in a self-supervised fashion, only from incomple...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2022-05-01
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| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/V-2-2022/143/2022/isprs-annals-V-2-2022-143-2022.pdf |