Based on this, the research proposes a multi-task face recognition algorithm by combining multi-task deep learning on the basis of convolutional neural network, and analyzes its performance in four dimensions of face identity, age, gender, and fatigue state. The exper...
普通的verification验证任务只需要一张图片和一个ID匹配上就1,匹配不上就1。但是recognition识别还需要判断和正确的匹配得上还有其他的匹配不上。那么,验证任务你做到一百个样本有99%的识别度,对于识别任务你要对其他的图片也进行匹配。你的准确度就要求高了非常多,你对一百个样本除了真样本,还有假样本都要判断正确,...
《A Discriminative Feature Learning Approach for Deep Face Recognition》 一种用于深度人脸识别的判别性特征学习方法 作者 Yandong Wen、Kaipeng Zhang、Zhifeng Li 和 Yu Qiao 来自深圳市计算机视觉与专利重点实验室、中国科学院深圳先进技术研究院和香港中文大学 初读 摘要 卷积神经网络(CNNs)在计算机视觉领域被广泛...
什么是人脸识别?(What is face recognition?) One-Shot学习(One-shot learning) 人脸识别所面临的一个挑战就是你需要解决一次学习问题,这意味着在大多数人脸识别应用中,你需要通过单单一张图片或者单单一个人脸样例就能去识别这个人。而历史上,当深度学习只有一个训练样例时,它的表现并不好,让我们看一个直观的例...
《A Discriminative Feature Learning Approach for Deep Face Recognition》论文笔记,程序员大本营,技术文章内容聚合第一站。
The experiment indicates that compared with real face data, the reconstruction face model has a small matching error by using SDAE algorithm and it achieves an excellent face recognition effect. 展开 关键词: 3D face depth data deep learning neural networks stacked denoising autoencoder unsupervised ...
2015---Deepid3_Face recognition with very deep neural networks 2015---EmotioNet_ An accurate, real-time algorithm for the automatic annotation of a million facial expressions in the wild 2015---Face++---Naive-Deep Face Recognition_Touching the Limit of LFW Benchmark or Not 2015---FaceNet--...
joint supervision of softmax loss and center loss, we can train a robust CNNs to obtain the deep features with the two key learning objectives, inter-class dispension and intra-class compactness as much as possible, which are very essential to face recognition. It is encouraging to see that...
A Novel Sparse Representation Classification Face Recognition Based on Deep Learning A novel sparse recognition face recognition algorithm based on deep learning is presented in this paper. The deep learning network extracted global and local... J Zeng,Y Zhai,J Gan - IEEE International Conference on...
原文: A Discriminative Feature Learning Approach for Deep Face Recognition 用于人脸识别的center loss。 1)同时学习每个类的深度特征的中心点 2)对深度特征和其对应的类中心的距离有一定的惩罚 提出的center loss函数在CNN中可以训练并且很容易优化。