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3D Face Reconstruction in Deep Learning Era: A Survey.

Sahil SharmaVijay Kumar
Published in: Archives of computational methods in engineering : state of the art reviews (2022)
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.
Keyphrases
  • deep learning
  • artificial intelligence
  • convolutional neural network
  • optical coherence tomography
  • current status