This paper proposes an encoder-decoder network to disentangle shape features during 3D face reconstruction from single 2D images, such that the tasks of reconstructing accurate 3D face shapes and learning discriminative shape features for face recognition can be accomplished simultaneously. Unlike existing 3D face reconstruction methods, our proposed method directly regresses dense 3D face shap...

The area of face recognition is one the most widely researched areas in domain computer vision and biometric. This because non-intrusive nature biometric makes it comparatively more suitable for application surveillance at public places such as airports. primitive methods could not give very satisfactory performance. However, with advent machine deep learning their recognition, several major br...

We introduce a novel approach to face models, which exploits the use of Partial Differential Equations (PDE) to generate the 3D face. This addresses some common problems of existing face models. The PDE face benefits from seamless merging of surface patches by using only a relatively small number of parameters based on boundary curves. The PDE face also provides users with a great degree of fre...

Accurate and plausible 3D face reconstruction remains a difficult problem up to this day, despite the tremendous advances in computer technology and the continuous growth of the applications utilizing 3D face models (e.g. biometrics, movies, gaming). In this paper, a two-step technique for efficient 3D face reconstruction from a set of face images acquired using an uncalibrated camera is presen...