A Deep Learning Approach to Facial 3D Reconstruction and Super-Resolution Rendering

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  • A Deep Learning Approach to Facial 3D Reconstruction and Super-Resolution Rendering Book Detail

  • Author : Tomoyori Iwao
  • Release Date : 2022
  • Publisher :
  • Genre :
  • Pages : 0
  • ISBN 13 :
  • File Size : 50,50 MB

A Deep Learning Approach to Facial 3D Reconstruction and Super-Resolution Rendering by Tomoyori Iwao PDF Summary

Book Description: Reconstructing 3D facial shapes is of significant interest in Computer Vision and Computer Graphics. In recent years, deep learning methods have been proposed for cost-effectively acquiring accurate 3D facial shapes. To some extent, these methods can generate accurate 3D facial shapes from a single image. Most of them assume that the resolution of the input images is high enough to reconstruct facial shapes, but this is not always the case, such as in the 3D reconstruction of players in a dynamic sports scene. Due to the large distances between players, one normally cannot acquire a photo showing all the players in focus and some faces could appear blurry. To tackle this problem, we propose a new learning-based architecture that combines a Super-Resolution (SR) network with a 3D Facial Reconstruction (FR) network. First, we input a low-resolution facial photo to the SR network, which generates corresponding SR images. These are input to the FR network, which generates corresponding facial shapes. We generate multiple SR images and corresponding 3D facial shapes because the SR network is a non-deterministic algorithm whose output is not always optimal for 3D reconstruction and rendering. Hence, we choose the best pair considering the noise level of the SR images and the distribution of distances among those facial shapes in order to reconstruct a good-quality 3D facial shape despite the low resolution of the input image.

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