3D Face Recognition

3D face recognition aims to identify individuals using three-dimensional facial data, offering potential advantages over 2D methods. Current research focuses on improving the robustness of these systems by addressing challenges like noisy depth data through techniques such as denoising networks and multi-modal fusion, and enhancing the controllability and realism of 3D face generation models using diffusion-based approaches. However, significant attention is also devoted to understanding and mitigating vulnerabilities, including attacks via 3D face morphing and adversarial perturbations using optical illusions or 3D-printed objects. These efforts are crucial for developing secure and reliable 3D face recognition systems with broad applications in security and other fields.