Speech Driven 3D Face Animation

Speech-driven 3D face animation aims to realistically animate a 3D face model based solely on audio input, striving for accurate lip-sync and emotionally expressive facial movements. Recent research heavily utilizes diffusion models and variational autoencoders (VAEs), often incorporating techniques like contrastive learning for personalization and classifier-free guidance for stylistic control, to overcome limitations of previous deterministic approaches. This field is advancing the creation of more realistic and emotionally nuanced virtual avatars for applications ranging from video conferencing and gaming to animation and film production. The development of large-scale datasets and improved model architectures are key focuses driving progress.