Face Reenactment

Face reenactment aims to realistically transfer facial expressions and movements from one video (the driving video) onto a different face (the source image), preserving the source's identity. Current research heavily utilizes generative adversarial networks (GANs) and diffusion models, often incorporating 3D facial models and techniques like motion warping or latent space manipulation for improved realism and control. This field is significant due to its applications in video editing, animation, and virtual reality, while also raising ethical concerns regarding deepfakes and the need for robust detection methods.