Talking Face Video

Talking face video generation aims to synthesize realistic videos of a person speaking, driven by audio input. Current research focuses on improving lip synchronization and visual fidelity using various approaches, including diffusion models, neural radiance fields (NeRFs), and transformer-based architectures, often incorporating optical flow for smoother transitions and attention mechanisms for enhanced feature extraction. These advancements have significant implications for applications such as virtual avatars, video conferencing, and film production, while also raising concerns about deepfake detection and the ethical implications of realistic video manipulation.