2020/10/12 by Renwang Chen, Xuanhong Chen, Bingbing Ni +1 · 1 voice · 1 citation
Computer Science · #Face and Expression Recognition #Face recognition and analysis #Generative Adversarial Networks and Image Synthesis #cs.CV
paper · pdf · doi:10.1145/3394171.3413630
openalex publication_date 2020/10/12 · openalex created_date 2020/10/22 · arxiv published 2021/06/11 · arxiv updated 2021/06/11 · openalex updated_date 2026/08/02
We propose an efficient framework, called Simple Swap (SimSwap), aiming for generalized and high fidelity face swapping. In contrast to previous approaches that either lack the ability to generalize to arbitrary identity or fail to preserve attributes like facial expression and gaze direction, our framework is capable of transferring the identity of an arbitrary source face into an arbitrary target face while preserving the attributes of the target face. We overcome the above defects in the following two ways. First, we present the ID Injection Module (IIM) which transfers the identity information of the source face into the target face at feature level. By using this module, we extend the architecture of an identity-specific face swapping algorithm to a framework for arbitrary face swapping. Second, we propose the Weak Feature Matching Loss which efficiently helps our framework to preserve the facial attributes in an implicit way. Extensive experiments on wild faces demonstrate that our SimSwap is able to achieve competitive identity performance while preserving attributes better than previous state-of-the-art methods.