… In this article, matrices and vectors are represented with capital bold and lowercase … , “Discriminative
multimanifold analysis for face recognition from a single training sample per person,…

… in virtual sample methods, domain adaption in generic learning … and further used light
angle vectors to represent intra-class … , there is only one sample per person in the gallery set. …

… length vector then we use the face embedding to recognize faces. … generic learning for face
recognition from a single sample … , ‘‘Discriminative multimanifold analysis for face recognition …

… Generic learning methods use an auxiliary dataset to make multiple samples for each person
to extract discriminative … We propose a method that extracts a feature vector with an evident …

… to generic learning method, which uses prototype and variation dictionary (P+V) model for
face recognition. … Second, aiming at the problem that the discriminative ability of atoms in …

… , nearest neighbors, support vector machine, and SoftMax loss) … way of finely learning
discriminative features adaptive to the … for face recognition from a single example image per …

… leverage them for discriminative learning or feature extraction… v to fool D to output a constant
vector with a uniform … feature for face recognition with single sample per person,” Pattern …

… more discriminative features from single samples based on … (HOG) features and employ
support vector machine (SVM) for … samples per person database, CelebA, as the generic data …

… to assist in learning representations that are discriminative in … Here, the noise vector z,
which we draw from a uniform … feature for face recognition with single sample per person,” …

… penalty to enhance the discriminative feature embedding. The … type vector can easily remember
all samples within one class [… feature embedding as a generic approach. On MegaFace, …