论文标题
通过验证的编码器通过图像来识别家庭
Recognizing Families through Images with Pretrained Encoder
论文作者
论文摘要
亲属验证和亲属检索是计算机视觉中的新兴任务。亲属验证旨在确定两个面部图像是否来自相关人员，而亲属检索是从图像画廊中检索可能的相关面部图像的任务。他们引入了独特的挑战，因为隐藏的关系和特征在面部图像之间具有固有的特征。我们采用3种方法，面部，暹罗VGG-Face以及FaceNet和VGG-FACE模型作为功能提取器的组合，以实现第9阶段的亲属验证和第5位，以在2020年野外竞争中获得公认家庭的亲属检索。然后，我们进一步使用stylegan2作为另一个编码器进行了实验，结果没有改善。
Kinship verification and kinship retrieval are emerging tasks in computer vision. Kinship verification aims at determining whether two facial images are from related people or not, while kinship retrieval is the task of retrieving possible related facial images to a person from a gallery of images. They introduce unique challenges because of the hidden relations and features that carry inherent characteristics between the facial images. We employ 3 methods, FaceNet, Siamese VGG-Face, and a combination of FaceNet and VGG-Face models as feature extractors, to achieve the 9th standing for kinship verification and the 5th standing for kinship retrieval in the Recognizing Family in The Wild 2020 competition. We then further experimented using StyleGAN2 as another encoder, with no improvement in the result.
