Triplet Loss首次在FaceNet: A Unified Embedding for Face Recognition and Clustering这篇论文中被提出,目的是使网络学到更好的人脸表征,即同一个人的不同输入通过网络输出的 表征间距离尽量小,不同人得到的 表征距离尽量大。 不同于Contrastive Loss,Triplet Loss构造了一个三元组计算损失。<a,p,n>分别表示ancho...
(anchor,positive,negative,alpha):#(随机选取的人脸样本的特征,anchor的正、负样本的特征) #它们的形状都是(batch_size,feature_size),feature_size是网络学习的人脸特征的维数 """Calculate the triplet loss according to the FaceNet paper with tf.variable_scope('triplet_loss'): pos_dist = tf.reduce_su...
Triplet-Center Loss for Multi-View 3D Object RetrievalXinwei He Yang Zhou ∗ Zhichao Zhou Song Bai Xiang BaiHuazhong University of Science and Technology{eriche.hust, zhouyangvcc}@gmail.com {zhichaozhou,songbai,xbai}@hust.edu.cnAbstractMost existing 3D object recognition algorithms focus onlevera...
In this paper, we put forward a novel loss function, called dual-modality hard mining triplet-center loss (DTCL), to optimize intra-class and inter-class distance and to supervise the network to learn discriminative feature representations. The DTCL learns a visible modality center and an ...
Triplet-Center Loss for Multi-View 3D Object Retrieval Xinwei He Yang Zhou∗ Zhichao Zhou Song Bai Xiang Bai Huazhong University of Science and Technology {eriche.hust, zhouyangvcc}@gmail.com {zhichaozhou,songbai,xbai}@hust.edu.cn Abstract Most existing 3D object recognition algorithms focus ...
Most existing 3D object recognition algorithms focus on leveraging the strong discriminative power of deep learning models with softmax loss for the classification of 3D data, while learning discriminative features with deep metric learning for 3D object retrieval is more or less neglected. In the pap...
It inherits the triplet-center loss property to achieve larger inter-class distance and smaller intra-class distance simultaneously. Unlike previous metric loss utilized in 3D shape retrieval methods, where Euclidean distance is adopted and the margin design is difficult, the proposed method is more ...
介绍了三元损失(triplet loss)和中心损失(center loss), 并整合提出了新的triplet-center loss(TCL),通过loss来学习每一类的中心点,并使得类内距离(intra-class distance)尽可能小,类间距离(inter-class distance)尽可能大。 提高了特征的区分度(discriminative power) - 相关工作 针对3D object retrieval,现阶段深...
triplet_loss (anchor, positive, negative, alpha): #(随机选取的人脸样本的特征,anchor的正、负样本的特征) #它们的形状都是(batch_size,feature_size),feature_size是网络学习的人脸特征的维数 """Calculate the triplet loss according to the FaceNet paper ...
Center triplet lossPerson re-identification(Re-ID) has been a hot topic in the field of computer vision for the past few years. In order to solve the problem of misalignment between different images, most of the existing algorithms use a certain method to manually divide the image into ...