论文标题
进化潜在空间搜索驱动人类肖像的生成
Evolutionary latent space search for driving human portrait generation
论文作者
论文摘要
本文介绍了一种基于生成对抗网络的潜在空间探索，用于合成人类肖像生成的进化方法。这个想法是产生与给定目标肖像非常相似的不同人脸图像。该方法适用于STYLAR2的肖像生成和面部相似性评估。进化搜索是基于探索stylegan2的真实编码的潜在空间。合成图像和真实图像的主要结果表明，所提出的方法产生了准确而多样的解决方案，代表了现实的人类肖像。拟议的研究可以有助于提高面部识别系统的安全性。
This article presents an evolutionary approach for synthetic human portraits generation based on the latent space exploration of a generative adversarial network. The idea is to produce different human face images very similar to a given target portrait. The approach applies StyleGAN2 for portrait generation and FaceNet for face similarity evaluation. The evolutionary search is based on exploring the real-coded latent space of StyleGAN2. The main results over both synthetic and real images indicate that the proposed approach generates accurate and diverse solutions, which represent realistic human portraits. The proposed research can contribute to improving the security of face recognition systems.
