Face Model

Face models are mathematical representations of human faces used for various tasks like recognition, alignment, and generation. Current research focuses on improving model accuracy and robustness, particularly addressing challenges like mask occlusion, pose variation, and limited training data. This is achieved through advancements in generative models (e.g., GANs, diffusion models, VAEs), incorporating attention mechanisms, and developing techniques for disentangling factors like identity and expression. These improvements have significant implications for applications ranging from security systems and virtual reality to personalized digital avatars and accessibility tools.