Face morphing attacks pose a significant threat to face recognition systems. In order to solve this problem, several methods for detecting these attacks have been proposed. However, the restoration of the accomplice’s face image remains in its nascent developmental stage. In this paper, we introduce a novel network architecture termed DFS-Net, which leverages double feature spaces (latent code and feature tensor) and a dual-feature separation (DFS) network. DFS-Net is built upon the StyleGAN2 generator. By utilizing the feature vector and feat...
