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3D Face Reconstruction System Based on Deep Learning and Sparse Face Model

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DOI: 10.23977/acsat.2017.1011


Sun Guangmin, Shi Xiuwen, Sun Yuge

Corresponding Author

Guangmin Sun


3D face reconstruction technology is very popular in the digital image processing area. The method of 3D face reconstruction based on single image faces many challenges such as: (i) depth information is lacked due to the input of 2D image; (ii) the statistical face model is not accurate; and (iii) many current difficulties can be solved by using new technique like deep learning. In order to get an accurate and efficient 3D face reconstruction result, a new 3D face reconstruction algorithm based on deep learning and sparse 3D face model is proposed in this paper. Deep learning is exploited to find out the statistical property of 3D human face. And sparse 3D face model is applied to improve algorithm efficiency. Experiments under different conditions are performed to prove the accuracy and robustness of our proposed algorithm.


Face Reconstruction, Deep Learning, Sparse 3D Face Model.

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