Facial morphe via domain translation and FM2RLS

Wei Zhang, Huabing Zhou
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Abstract

In this paper, we present a novel approach for face morphe. We use a recent domain transfer technique to generate target expression and combine a robust image deformation technique to obtain high realistic facial morphe. We addressed the facial morphe problem through three steps. Firstly, Domain transfer technique is introduced to transfer an image from one domain to another. Secondly, use a face alignment algorithm to locate accurate facial landmark points for both domain transferred face and target face, then align them with a global similarity transformation to eliminate their inconsistency in pose, size and position. Then we employ the FM2RLS method to deform the domain transferred face into the target image, let the images pairs align in pixel level. To validate the effectiveness of the proposed approach, extensive experiments on real images shows accurate results of our method, which is superior to the current state-of-the-art methods.
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基于域翻译和FM2RLS的面部形态
本文提出了一种新的人脸形态识别方法。我们使用最新的领域转移技术来生成目标表情,并结合鲁棒图像变形技术来获得高真实感的面部形态。我们通过三个步骤解决了面部变形问题。首先,引入域转移技术,将图像从一个域转移到另一个域。其次,利用人脸对齐算法对域转移人脸和目标人脸进行精确的人脸地标点定位,利用全局相似度变换对其进行对齐,消除它们在姿态、大小和位置上的不一致;然后利用FM2RLS方法将转移域的人脸变形为目标图像,使图像对在像素级上对齐。为了验证该方法的有效性,在真实图像上进行了大量的实验,结果表明该方法的结果准确,优于目前最先进的方法。
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Image fusion for multimodality image via domain transfer and nonrigid transformation Dimensionality reduction of hyperspectral images based on subspace combination clustering and adaptive band selection Remote multi-object detection based on bounding box field Facial morphe via domain translation and FM2RLS Restoration of haze-free images using generative adversarial network
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