Reference-guided Face Component Editing | |
Deng, Qiyao1,3; Cao, Jie1,3; Liu, Yunfan1,3; Chai, Zhenhua2; Li, Qi1,3; Sun, Zhenan1,3 | |
2020 | |
会议日期 | 2021年1月7日 – 2021年1月15日 |
会议地点 | 日本横滨 |
英文摘要 | Face portrait editing has achieved great progress in recent years. However, previous methods either 1) operate on pre-defined face attributes, lacking the flexibility of controlling shapes of high-level semantic facial components (e.g., eyes, nose, mouth), or 2) take manually edited mask or sketch as an intermediate representation for observable changes, but such additional input usually requires extra efforts to obtain. To break the limitations (e.g. shape, mask or sketch) of the existing methods, we propose a novel framework termed r-FACE (Reference-guided FAce Component Editing) for diverse and controllable face component editing with geometric changes. Specifically, r-FACE takes an image inpainting model as the backbone, utilizing reference images as conditions for controlling the shape of face components. In order to encourage the framework to concentrate on the target face components, an example-guided attention module is designed to fuse attention features and the target face component features extracted from the reference image. Through extensive experimental validation and comparisons, we verify the effectiveness of the proposed framework. |
语种 | 英语 |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/44727] |
专题 | 自动化研究所_智能感知与计算研究中心 |
通讯作者 | Li, Qi |
作者单位 | 1.中国科学院大学 2.美团AI平台 3.中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Deng, Qiyao,Cao, Jie,Liu, Yunfan,et al. Reference-guided Face Component Editing[C]. 见:. 日本横滨. 2021年1月7日 – 2021年1月15日. |
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