Face Editing

Face editing research focuses on developing algorithms and models to modify facial images and videos realistically and controllably. Current efforts concentrate on improving the fidelity and consistency of edits using diffusion models, GANs (Generative Adversarial Networks), and neural radiance fields (NeRFs), often incorporating techniques like semantic segmentation and 3D modeling for more precise and localized manipulation. This field is significant for its applications in various domains, including entertainment, forensics, and medical imaging, as well as for its contributions to understanding human perception and image generation. The development of robust and ethical face editing tools is crucial given the potential for misuse in areas such as deepfakes and misinformation.