Self-supervised Learning of Detailed 3D Face Reconstruction
In this paper, we present an end-to-end learning framework for detailed 3D face reconstruction from a single image1. Our approach uses a 3DMM-based coarse model and a displacement map in UV-space to represent a 3D face. Unlike previous work addressing the problem, our learning framework does not req...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - PP(2020) vom: 27. Aug.
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| 1. Verfasser: |
Chen, Yajing
(VerfasserIn) |
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| Weitere Verfasser: |
Wu, Fanzi,
Wang, Zeyu,
Song, Yibing,
Ling, Yonggen,
Bao, Linchao |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2020
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
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| Schlagworte: | Journal Article |
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