3D Face Reconstruction in Deep Learning Era: A Survey

3D face reconstruction is the most captivating topic in biometrics with the advent of deep learning and readily available graphical processing units. This paper explores the various aspects of 3D face reconstruction techniques. Five techniques have been discussed, namely, deep learning, epipolar geometry, one-shot learning, 3D morphable model, and shape from shading methods. This paper provides an in-depth analysis of 3D face reconstruction using deep learning techniques. The performance analysis of different face reconstruction techniques has been discussed in terms of software, hardware, pros and cons. The challenges and future scope of 3d face reconstruction techniques have also been discussed.

Automated summary

This paper thoroughly explores the topic of 3D face reconstruction, covering various techniques such as deep learning, epipolar geometry, one-shot learning, 3D morphable model, and shape from shading methods. It provides a performance analysis of different techniques and discusses the challenges and future scope of 3D face reconstruction.