The quality and size of training set have a great impact on the results of deep learning-
based face-related tasks. However, collecting and labeling adequate samples with high …

This paper addresses the problem of face recognition when there is only few, or even only a
single, labeled examples of the face that we wish to recognize. Moreover, these examples …

During the past several years, as one of the most successful applications of sparse coding
and dictionary learning, dictionary-based face recognition has received significant attention …

With the aid of a universal facial variation dictionary, sparse representation based classifier
(SRC) has been naturally extended for face recognition (FR) with single sample per person …

The quality and size of training set have great impact on the results of deep learning-based
face related tasks. However, collecting and labeling adequate samples with high quality and …

Recent research has demonstrated the effectiveness of linear representation (ie, sparse
representation, group sparse representation and collaborative representation) for face …

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虹膜和指纹等生物特征已成为人们进入万物互联世界的数字身份证. 生物特征识别赋予机器自动 …

Single sample face recognition (SSFR) is a challenging research problem in which only one
face image per person is available for training. Moreover, the face image may have different …

A linear regression-based method is a hot topic in face recognition community. Recently,
sparse representation and collaborative representation-based classifiers for face recognition …

Single-sample face recognition is one of the most challenging problems in face recognition.
We propose a novel algorithm to address this problem based on a sparse representation …