1. A method for 3D-aided 2D face recognition under large pose and illumination variations implemented on a computer or on a distributed computer network, where the method comprises: enrolling a face of a subject into a gallery database as a fitted annotated face model, where the enrollment data comprises raw 3D data obtained either from a 3D scanner or imaging apparatus or derived from a 2D imaging or scanning apparatus and where a statistically derived annotated face model is fitted using a subdivision-based deformable model framework to the raw 3D data, if the raw 3D data includes over-saturated specular highlights, inpainting the albedo texture to produce an estimated the lighting invariant albedo texture, obtaining raw 2D data of a target face from a 2D imagining or scanning apparatus or probe, lifting a texture of the target face from the 2D probe image, selecting a specific fitted annotated face model from the gallery for an authentication experiment or all the gallery models for an identification experiment, bidirectionally relighting the gallery texture from the selected specific fitted annotated face model to change an illumination of the gallery texture to match the texture lifted from the probe image, comparing the two matched textures, and verifying and/or identifying the target face based on a value of a metric.