CR-GAN: Automatic craniofacial reconstruction for personal identification

作者：

Highlights：

• Deep adversarial learning technique is introduced to synthesize the face images from the skull images for automated craniofacial reconstruction.

• Artificial neural network architecture and one-to-many inference approach are designed.

• Through comprehensive automated face recognition tests on five deep face recognition algorithms for the recreated face, we demonstrate the effectiveness of the proposed approach.

摘要

•Deep adversarial learning technique is introduced to synthesize the face images from the skull images for automated craniofacial reconstruction.•Artificial neural network architecture and one-to-many inference approach are designed.•Through comprehensive automated face recognition tests on five deep face recognition algorithms for the recreated face, we demonstrate the effectiveness of the proposed approach.

论文关键词：Craniofacial reconstruction,CT scans,Deep learning

论文评审过程：Received 19 April 2021, Revised 14 September 2021, Accepted 24 October 2021, Available online 26 October 2021, Version of Record 28 February 2022.

论文官网地址：https://doi.org/10.1016/j.patcog.2021.108400