Pareidolia Face Reenactment | |
Song, Linsen1,2![]() ![]() ![]() | |
2021 | |
会议名称 | IEEE Conference on Computer Vision and Pattern Recognition |
会议日期 | 2021.6.19 |
会议地点 | 线上 |
摘要 | We present a new application direction named Pareidolia Face Reenactment, which is defined as animating a static illusory face to move in tandem with a human face in the video. For the large differences between pareidolia face reenactment and traditional human face reenactment, two main challenges are introduced, i.e., shape variance and texture variance. In this work, we propose a novel Parametric Unsupervised Reenactment Algorithm to tackle these two challenges. Specifically, we propose to decompose the reenactment into three catenate processes: shape modeling, motion transfer and texture synthesis. With the decomposition, we introduce three crucial components, i.e., Parametric Shape Modeling, Expansionary Motion Transfer and Unsupervised Texture Synthesizer, to overcome the problems brought by the remarkably variances on pareidolia faces. Extensive experiments show the superior performance of our method both qualitatively and quantitatively. Code, model and data are available on our project page. |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48686 |
专题 | 模式识别实验室 |
通讯作者 | He, Ran |
作者单位 | 1.School of Artificial Intelligence, University of Chinese Academy of Sciences 2.NLPR & CRIPAC, CASIA 3.SenseTime Research 4.S-Lab, Nanyang Technological University |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Song, Linsen,Wu, Wayne,Fu, Chaoyou,et al. Pareidolia Face Reenactment[C],2021. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
CVPR_PFR.pdf(5601KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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