Personalized facial makeup transfer based on outline correspondence
Most existing makeup transfer techniques focus on light makeup styles, which limits the task of makeup transfer to color manipulation issues such as eye shadow and lip gloss. However, the makeup in real life is diverse and personalized, not only the most basic foundation, eye makeup, but also the pa...
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Published in | Computer animation and virtual worlds Vol. 35; no. 1 |
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Main Authors | , |
Format | Journal Article |
Language | English |
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01.01.2024
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Abstract | Most existing makeup transfer techniques focus on light makeup styles, which limits the task of makeup transfer to color manipulation issues such as eye shadow and lip gloss. However, the makeup in real life is diverse and personalized, not only the most basic foundation, eye makeup, but also the painted patterns on the face, jewelry decoration and other personalized makeup. Inspired by the painting steps of drawing the outline first and then coloring, we propose a makeup transfer network for personalized makeup, which realizes face makeup transfer by learning outline correspondence. Specifically, we propose the outline feature extraction module and outline loss that can promote outline correspondence. Our network can not only transfer daily light makeup, but also complete transfer for complex facial painting patterns. Experiments show that our method can obtain visually more accurate makeup transfer results. Quantitative and qualitative experimental results show that the method proposed in this paper achieves superior results in extreme makeup transfer compared to the state‐of‐the‐art methods.
In this paper, we propose a novel makeup transfer method, which first extracts the outline features of the images, and then establishes the outline correspondence between the two images through the self‐attention mechanism. Our method successfully solves the problem of incomplete transfer of colored patterns in the task of extreme makeup transfer. Experiments demonstrate that the method can not only transfer extreme makeup, but also transfer daily light makeup well. |
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AbstractList | Most existing makeup transfer techniques focus on light makeup styles, which limits the task of makeup transfer to color manipulation issues such as eye shadow and lip gloss. However, the makeup in real life is diverse and personalized, not only the most basic foundation, eye makeup, but also the painted patterns on the face, jewelry decoration and other personalized makeup. Inspired by the painting steps of drawing the outline first and then coloring, we propose a makeup transfer network for personalized makeup, which realizes face makeup transfer by learning outline correspondence. Specifically, we propose the outline feature extraction module and outline loss that can promote outline correspondence. Our network can not only transfer daily light makeup, but also complete transfer for complex facial painting patterns. Experiments show that our method can obtain visually more accurate makeup transfer results. Quantitative and qualitative experimental results show that the method proposed in this paper achieves superior results in extreme makeup transfer compared to the state‐of‐the‐art methods. Most existing makeup transfer techniques focus on light makeup styles, which limits the task of makeup transfer to color manipulation issues such as eye shadow and lip gloss. However, the makeup in real life is diverse and personalized, not only the most basic foundation, eye makeup, but also the painted patterns on the face, jewelry decoration and other personalized makeup. Inspired by the painting steps of drawing the outline first and then coloring, we propose a makeup transfer network for personalized makeup, which realizes face makeup transfer by learning outline correspondence. Specifically, we propose the outline feature extraction module and outline loss that can promote outline correspondence. Our network can not only transfer daily light makeup, but also complete transfer for complex facial painting patterns. Experiments show that our method can obtain visually more accurate makeup transfer results. Quantitative and qualitative experimental results show that the method proposed in this paper achieves superior results in extreme makeup transfer compared to the state‐of‐the‐art methods. In this paper, we propose a novel makeup transfer method, which first extracts the outline features of the images, and then establishes the outline correspondence between the two images through the self‐attention mechanism. Our method successfully solves the problem of incomplete transfer of colored patterns in the task of extreme makeup transfer. Experiments demonstrate that the method can not only transfer extreme makeup, but also transfer daily light makeup well. |
Author | Gao, Mengying Wang, Pengjie |
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Cites_doi | 10.1109/WACV51458.2022.00317 10.1109/WACV51458.2022.00102 10.1109/ICCV.2017.304 10.1023/B:VISI.0000029664.99615.94 10.1109/CVPR42600.2020.00524 10.1109/CVPR46437.2021.01310 10.1007/978-3-030-01264-9_33 10.1109/CVPR.2017.544 10.1109/CVPR.2017.73 10.1109/CVPR.2019.00238 10.1109/TPAMI.2017.2724510 10.1109/CVPR42600.2020.00584 10.1145/3197517.3201332 10.1145/3240508.3240618 10.1109/CVPR.2018.00012 10.1609/aaai.v36i2.20131 10.1109/CVPR42600.2020.00519 10.1109/TIP.2003.819861 10.1109/TPAMI.2009.77 10.1109/TPAMI.2021.3083484 10.1145/3197517.3201365 10.1109/ICCV.2019.01058 10.1109/ICCV.2017.203 10.1109/CVPR.2019.00244 |
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Snippet | Most existing makeup transfer techniques focus on light makeup styles, which limits the task of makeup transfer to color manipulation issues such as eye shadow... |
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SubjectTerms | Customization Eye (anatomy) Feature extraction Gloss image to image translation makeup transfer semantic correspondence |
Title | Personalized facial makeup transfer based on outline correspondence |
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