Any-to-one Face Reenactment Based on Conditional Generative Adversarial Network | |
Tianxiang Ma1,2,3![]() ![]() ![]() | |
2019 | |
会议名称 | Asia- Pacific Signal and Information Processing Association Annual Summit and Conference |
会议日期 | 11.18-11.21 |
会议地点 | 中国兰州 |
摘要 | Face reenactment refers to the process of transferring the expressions and postures of a given face to the target face. We present a novel Any-to-one Face Reenactment Model based on Conditional Generative Adversarial Network, which has a simple dual converter structure: Any-to-one Face Landmarks Map Converter(AFLC) and Landmark-to-face Converter based on Conditional Generative Adversarial Network(LFC). The former transfers any source face into the landmarks map of the target face, and the map has the expression and posture attributes of the source face. The latter has a generator that transfers the landmarks map of the target face into the realistic and identity-preserving target facial image. The whole model is purely learning-based without any 3D model, and can generate high quality transferred face comparable to the state-of-the-art. What’s more the model is highly robust to wild faces, including various faces of different complexions, ages, and genders. We performed an ablation study on our proposed AFLC to verify its importance for face reenactment of any object. AFLC helps the overall model to achieve an effective facial reenactment. |
七大方向——子方向分类 | 图像视频处理与分析 |
国重实验室规划方向分类 | 视觉信息处理 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/56668 |
专题 | 模式识别实验室 |
通讯作者 | Jing Dong |
作者单位 | 1.National Laboratory of Pattern Recognition, CASIA 2.Center for Research on Intelligent Perception and Computing, CASIA 3.University of Chinese Academy of Sciences, Beijing, 100049, China |
第一作者单位 | 中国科学院自动化研究所; 模式识别国家重点实验室 |
通讯作者单位 | 中国科学院自动化研究所; 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Tianxiang Ma,Bo Peng,Wei Wang,et al. Any-to-one Face Reenactment Based on Conditional Generative Adversarial Network[C],2019. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Any-to-one_Face_Reen(2241KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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