Face Image Synthesis

Face image synthesis focuses on generating realistic and high-fidelity synthetic faces, often using Generative Adversarial Networks (GANs) and increasingly, Neural Radiance Fields (NeRFs). Current research emphasizes improving realism, mitigating biases (like gender and age imbalances) in generated datasets, and enhancing control over identity and expression, including the ability to synthesize talking faces synchronized with audio. This field is significant due to its applications in media creation, dataset augmentation for training image analysis models, and its potential to contribute to the development of more robust and ethical AI systems, while also raising concerns about the detection of synthetic media.