KinshipGAN:亲子人脸生成器-从父母照片生成未来孩子的人脸图像Synthesizing of Kinship Faces From Family Photos by Regularizing a Deep Face Network

本文提出了一种亲属人脸生成器网络, 可以通过分析父母的照片来合成可能的儿童脸。为此, 我们重点讨论了在整个论文中, 通过提出新的解决方案来处理亲属关系数据的稀缺性问题。为了提取鲁棒特性, 我们将预先训练的脸部模型集成到亲属脸生成器中。此外, 发电机组网络的规范化与附加面数据集和对抗损失, 以减少样本较少带来overfitting。最后, 我们对循环域变换进行了调整, 以达到更稳定的结果。对开放 (FIW) 数据集内的家庭进行了实验。实验结果表明, 与基线算法相比, 本文提出的方法具有重要的性能改进, 我们提出的方法具有良好的视觉感知效果。

以后亲子照就不用父母双方照片生硬合成了,交给KinshipGAN吧!

Savas Ozkan, Akin Ozkan
In this paper, we propose a kinship generator network that can synthesize a possible child face by analyzing his/her parent’s photo. For this purpose, we focus on to handle the scarcity of kinship datasets throughout the paper by proposing novel solutions in particular. To extract robust features, we integrate a pre-trained face model to the kinship face generator. Moreover, the generator network is regularized with an additional face dataset and adversarial loss to decrease the overfitting of the limited samples. Lastly, we adapt cycle-domain transformation to attain a more stable results. Experiments are conducted on Families in the Wild (FIW) dataset. The experimental results show that the contributions presented in the paper provide important performance improvements compared to the baseline architecture and our proposed method yields promising perceptual results.
看看效果如何:
Several visual outputs of the proposed method for father-daughter, father-son, mother-daughter and mother-son. You can also find the opposite gender of the results.

转载请注明:《KinshipGAN:亲子人脸生成器-从父母照片生成未来孩子的人脸图像Synthesizing of Kinship Faces From Family Photos by Regularizing a Deep Face Network

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