Facial Depth

Facial depth analysis focuses on accurately capturing and utilizing three-dimensional facial geometry from various image sources, aiming to improve applications like face recognition and manipulation detection. Current research emphasizes developing robust methods for depth map generation and denoising, often employing convolutional neural networks (CNNs) with innovative modules like attention mechanisms and incorporating complementary information from RGB images and segmentation masks. These advancements are driving improvements in the accuracy and robustness of facial recognition systems, as well as enabling new applications such as detecting manipulated images and enhancing clinical procedures.