In recent years, talking head generation has become a focal point for researchers. Considerable effort is being made to refine lip-sync motion, capture expressive facial expressions, generate natural head poses, and achieve high video quality. However, no single model has yet achieved equivalence across all these metrics. This paper aims to animate a 3D face using Jamba, a hybrid Transformers-Mamba model. Mamba, a pioneering Structured State Space Model (SSM) architecture, was designed to address the constraints of the conventional Transformer architecture. Nevertheless, it has several drawbacks. Jamba merges the advantages of both Transformer and Mamba approaches, providing a holistic solution. Based on the foundational Jamba block, we present JambaTalk to enhance motion variety and speed through multimodal integration. Extensive experiments reveal that our method achieves performance comparable or superior to state-of-the-art models.
View on arXiv