基于二维密集映射的人脸替换

Han Guo, Dongmei Niu, Xiangyu Kong, Xiuyang Zhao
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引用次数: 3

摘要

换脸,又称换脸,是一个在隐私保护、智能人机交互、视频效果等方面值得投资的问题。本文提出了一种新的方法,在保留姿态和面部特征的同时,将输入图像的身份转换为目标身份。认为二维人脸替换可以用三维变形模型投影的二维图形密集映射问题代替。该方法采用平面参数化和仿射变换的方法,在二维图形之间建立了一对一的密集映射。它可以在不进行图像预处理的情况下减少对非正面人脸旋转的影响。然后,我们的方法调整眼睛的位置以保持输入图像的凝视方向,并基于无缝克隆将变换后的图像与目标图像缝合,以显示图像的真实性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Face replacement based on 2D dense mapping
Face replacement, also known as face swapping, is a worth investing problem in privacy protection, intelligent human-computer interaction and video effects. In our paper, a new approach is proposed to transform identities of the input images into a target identity while preserving poses and facial features. It is considered that 2D face replacement can be replaced by the problem of 2D graphics dense mapping using 3D morphable models projection. For mapping the input facial region and the target, our method uses planar parameterization and affine transformation to establish a one-to-one dense mapping between 2D graphics. It can enable to reduce the effect on the rotation of non-frontal faces without image preprocessing. Our method then adjusts positions of eyes to keep gaze direction of the input images, and stitches the transformed image and the target image based on seamless cloning to show the authenticity of the images.
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