公开(公告)号：US11600113B2

公开(公告)日：2023-03-07

申请号：US17091066

申请日：2020-11-06

Applicant: NEC Laboratories America, Inc.

Inventor： Xiang Yu ,  Manmohan Chandraker ,  Kihyuk Sohn ,  Aruni RoyChowdhury

IPC: G06V40/16 ,  G06K9/62 ,  G06N3/04 ,  G06N3/08

Abstract: A computer-implemented method for implementing face recognition includes obtaining a face recognition model trained on labeled face data, separating, using a mixture of probability distributions, a plurality of unlabeled faces corresponding to unlabeled face data into a set of one or more overlapping unlabeled faces that include overlapping identities to those in the labeled face data and a set of one or more disjoint unlabeled faces that include disjoint identities to those in the labeled face data, clustering the one or more disjoint unlabeled faces using a graph convolutional network to generate one or more cluster assignments, generating a clustering uncertainty associated with the one or more cluster assignments, and retraining the face recognition model on the labeled face data and the unlabeled face data to improve face recognition performance by incorporating the clustering uncertainty.

公开(公告)号：US20210142046A1

公开(公告)日：2021-05-13

申请号：US17091066

申请日：2020-11-06

Applicant: NEC Laboratories America, Inc.

Inventor： Xiang Yu ,  Manmohan Chandraker ,  Kihyuk Sohn ,  Aruni RoyChowdhury

IPC: G06K9/00 ,  G06K9/62 ,  G06N3/08 ,  G06N3/04

Abstract: A computer-implemented method for implementing face recognition includes obtaining a face recognition model trained on labeled face data, separating, using a mixture of probability distributions, a plurality of unlabeled faces corresponding to unlabeled face data into a set of one or more overlapping unlabeled faces that include overlapping identities to those in the labeled face data and a set of one or more disjoint unlabeled faces that include disjoint identities to those in the labeled face data, clustering the one or more disjoint unlabeled faces using a graph convolutional network to generate one or more cluster assignments, generating a clustering uncertainty associated with the one or more cluster assignments, and retraining the face recognition model on the labeled face data and the unlabeled face data to improve face recognition performance by incorporating the clustering uncertainty.