Hybrid Face Reflectance, Illumination, and Shape From a Single Image
We propose HyFRIS-Net to jointly estimate the hybrid reflectance and illumination models, as well as the refined face shape from a single unconstrained face image in a pre-defined texture space. The proposed hybrid reflectance and illumination representation ensure photometric face appearance modeli...
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 44(2022), 9 vom: 14. Sept., Seite 5002-5015 |
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| 1. Verfasser: | |
| Weitere Verfasser: | , , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2022
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
| Schlagworte: | Journal Article Research Support, Non-U.S. Gov't |
| Zusammenfassung: | We propose HyFRIS-Net to jointly estimate the hybrid reflectance and illumination models, as well as the refined face shape from a single unconstrained face image in a pre-defined texture space. The proposed hybrid reflectance and illumination representation ensure photometric face appearance modeling in both parametric and non-parametric spaces for efficient learning. While forcing the reflectance consistency constraint for the same person and face identity constraint for different persons, our approach recovers an occlusion-free face albedo with disambiguated color from the illumination color. Our network is trained in a self-evolving manner to achieve general applicability on real-world data. We conduct comprehensive qualitative and quantitative evaluations with state-of-the-art methods to demonstrate the advantages of HyFRIS-Net in modeling photo-realistic face albedo, illumination, and shape |
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| Beschreibung: | Date Completed 08.08.2022 Date Revised 14.09.2022 published: Print-Electronic Citation Status MEDLINE |
| ISSN: | 1939-3539 |
| DOI: | 10.1109/TPAMI.2021.3080586 |