Deep learning based approaches have been dominating the face recognition field due to
the significant performance improvement they have provided on the challenging wild …

This paper proposes to learn a set of high-level feature representations through deep
learning, referred to as Deep hidden IDentity features (DeepID), for face verification. We …

In modern face recognition, the conventional pipeline consists of four stages: detect=>
align=> represent=> classify. We revisit both the alignment step and the representation step …

It is unknown what kind of biases modern in the wild face datasets have because of their
lack of annotation. A direct consequence of this is that total recognition rates alone only …

This paper designs a high-performance deep convolutional network (DeepID2+) for face
recognition. It is learned with the identification-verification supervisory signal. By increasing …

Face images appearing in multimedia applications, eg, social networks and digital
entertainment, usually exhibit dramatic pose, illumination, and expression variations …

Face representation is a crucial step of face recognition sys tems. An optimal face
representation should be discrimina tive, robust, compact, and very easy to implement …

Face representation is a crucial step of face recognition systems. An optimal face
representation should be discriminative, robust, compact, and very easy-to-implement. While …

Face Recognition is one of the challenging process due to huge amount of wild datasets.
Deep learning has been provided good solution in terms of recognition performance, as day …

Face recognition with large pose and illumination variations is a challenging problem in
computer vision. This paper addresses this challenge by proposing a new learningbased …