Attribute-Aware Face Aging With Wavelet-Based Generative Adversarial Networks | |
Liu, Yunfan; Li, Qi; Sun, Zhenan | |
2019 | |
会议名称 | IEEE Conference On Computer Vision and Pattern Recognition |
会议日期 | 20190616-20190620 |
会议地点 | Long Beach, America |
摘要 | Since it is difficult to collect face images of the same subject over a long range of age span, most existing face aging methods resort to unpaired datasets to learn age mappings. However, the matching ambiguity between young and aged face images inherent to unpaired training data may lead to unnatural changes of facial attributes during the aging process, which could not be solved by only enforcing identity consistency like most existing studies do. In this paper, we propose an attribute-aware face aging model with wavelet based Generative Adversarial Networks (GANs) to address the above issues. To be specific, we embed facial attribute vectors into both the generator and discriminator of the model to encourage each synthesized elderly face image to be faithful to the attribute of its corresponding input. In addition, a wavelet packet transform (WPT) module is incorporated to improve the visual fidelity of generated images by capturing age-related texture details at multiple scales in the frequency space. Qualitative results demonstrate the ability of our model in synthesizing visually plausible face images, and extensive quantitative evaluation results show that the proposed method achieves state-of-the-art performance on existing datasets. |
关键词 | Face Aging |
收录类别 | EI |
七大方向——子方向分类 | 生物特征识别 |
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/173211/26091 |
专题 | 智能感知与计算研究中心 |
通讯作者 | Liu, Yunfan |
作者单位 | CASIA |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Liu, Yunfan,Li, Qi,Sun, Zhenan. Attribute-Aware Face Aging With Wavelet-Based Generative Adversarial Networks[C],2019. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Liu_Attribute-Aware_(3599KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 |
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