MaskGAN: Towards Diverse and Interactive Facial Image Manipulation
Cheng-Han Lee, Ziwei Liu, Lingyun Wu, Ping Luo
2020年份
205顶会引用
摘要
Style Copy Smiling Transfer (a) Target Image (a) Target Image (c) Modification on the mask (d) Result (c) Modification on the mask (d) Result (b) Source Image (b) Source Image Figure 1: Given a target image (a), users are allowed to modify masks of the target images in (c) according to the source images (b) so that we can obtain manipulation results (d). The left shows illustrative examples from "neutral" to "smiling", while the right shows style copy such as makeup, hair, expression, skin color, etc.
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引用它的顶会 Paper205
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- EditGAN: High-Precision Semantic Image EditingHuan Ling, Karsten Kreis, Daiqing Li, Seung Wook Kim 等NeurIPS 2021 · 被引用 248 次
- HeadNeRF: A Realtime NeRF-based Parametric Head ModelYang Hong, Bo Peng, Haiyao Xiao, Ligang Liu 等CVPR 2022 · 被引用 189 次
它引用的顶会 Paper3
- Free-Form Image Inpainting With Gated ConvolutionJiahui Yu, Zhe Lin, Jimei Yang, Xiaohui Shen 等ICCV 2019 · 被引用 1,990 次
- SC-FEGAN: Face Editing Generative Adversarial Network With User's Sketch and ColorYoungjoo Jo, Jongyoul ParkICCV 2019 · 被引用 325 次
- Towards Photo-Realistic Virtual Try-On by Adaptively Generating↔Preserving Image ContentHan Yang, Ruimao Zhang, Xiaobao Guo, Wei Liu 等CVPR 2020
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