RGB D Face Recognition

RGB-D face recognition aims to improve the accuracy and robustness of facial recognition systems by integrating depth information (from depth sensors) with traditional RGB images. Current research focuses on developing methods for accurate depth map generation from RGB images, efficient fusion of RGB and depth features (often using attention mechanisms or confidence weighting), and training robust models despite the scarcity of large-scale RGB-D face datasets. These advancements hold significant promise for enhancing the performance of face recognition in challenging real-world scenarios, such as those with varying lighting, occlusion, or pose, leading to more reliable and secure applications.