公开(公告)号：WO2018089289A1

公开(公告)日：2018-05-17

申请号：PCT/US2017/060104

申请日：2017-11-06

Applicant: NEC LABORATORIES AMERICA, INC

Inventor： XU, Xiang ,  SOHN, Kihyuk ,  CHANDRAKER, Manmohan ,  PENG, Xi

IPC: G06K9/00 ,  G06K9/62 ,  G06N3/02

Abstract: A computer-implemented method, system, and computer program product is provided for pose-invariant facial recognition. The method includes generating, by a processor using a recognition neural network (150), a rich feature embedding for identity information and non-identity information for each of one or more images. The method also includes generating, by the processor using a Siamese reconstruction network (160), one or more pose-invariant features (170) by employing the rich feature embedding for identity information and non-identity information. The method additionally includes identifying, by the processor, a user (180) by employing the one or more pose-invariant features. The method further includes controlling an operation of a processor-based machine to change a state of the processor-based machine, responsive to the identified user in the one or more images.

Abstract translation: 提供了用于姿态不变的面部识别的计算机实现的方法，系统和计算机程序产品。 该方法包括通过使用识别神经网络（150）的处理器为一个或多个图像中的每一个的身份信息和非身份信息生成丰富特征嵌入。 该方法还包括由处理器使用连体重建网络（160）通过将丰富特征嵌入用于身份信息和非身份信息来生成一个或多个姿势不变特征（170）。 该方法另外包括通过使用该一个或多个姿态不变特征来由处理器识别用户（180）。 该方法还包括响应于在一个或多个图像中识别的用户，控制基于处理器的机器的操作以改变基于处理器的机器的状态。

公开(公告)号：WO2021243029A1

公开(公告)日：2021-12-02

申请号：PCT/US2021/034528

申请日：2021-05-27

Applicant: NEC LABORATORIES AMERICA, INC.

Inventor： CHANDRAKER, Manmohan ,  WANG, Ting ,  XU, Xiang ,  PITTALUGA, Francesco ,  SHARMA, Gaurav ,  TSAI, Yi-Hsuan ,  FARAKI, Masoud ,  CHEN, Yuheng ,  TIAN, Yue ,  HUANG, Ming-Fang ,  FANG, Jian

IPC: G06K9/00 ,  G06N3/08

Abstract: Methods and systems for training a neural network include generating (801) an image of a mask. A copy of an image is generated (302) from an original set of training data. The copy is altered (302) to add the image of a mask to a face detected within the copy. An augmented set of training data is generated (302) that includes the original set of training data and the altered copy. A neural network model is trained (304) to recognize masked faces using the augmented set of training data.