Face Swapping

Face swapping, the technique of replacing one person's face in an image or video with another's, aims to create realistic and seamless manipulations. Current research focuses on improving the realism of swapped faces using diffusion models and generative adversarial networks (GANs), often incorporating techniques like latent code manipulation, attention mechanisms, and 3D morphable models to better control identity and attribute transfer. This field is significant due to its implications for both malicious applications (deepfakes) and beneficial uses (e.g., entertainment, privacy protection), driving the development of both improved swapping techniques and robust detection methods. The development of large-scale datasets and no-reference quality assessment metrics are also key areas of ongoing research.