US 11,710,346 B2
Facial recognition for masked individuals
Manmohan Chandraker, Santa Clara, CA (US); Ting Wang, West Windsor, NJ (US); Xiang Xu, Mountain View, CA (US); Francesco Pittaluga, Los Angeles, CA (US); Gaurav Sharma, Newark, CA (US); Yi-Hsuan Tsai, Santa Clara, CA (US); Masoud Faraki, San Jose, CA (US); Yuheng Chen, South Brunswick, NJ (US); Yue Tian, Princeton, NJ (US); Ming-Fang Huang, Princeton, NJ (US); and Jian Fang, Princeton, NJ (US)
Assigned to NEC Corporation
Filed by NEC Laboratories America, Inc., Princeton, NJ (US)
Filed on May 26, 2021, as Appl. No. 17/330,832.
Claims priority of provisional application 63/031,483, filed on May 28, 2020.
Prior Publication US 2021/0374468 A1, Dec. 2, 2021
Int. Cl. G06V 40/16 (2022.01); G06T 3/00 (2006.01); G06V 10/774 (2022.01)
CPC G06V 40/172 (2022.01) [G06T 3/0006 (2013.01); G06V 10/774 (2022.01); G06V 40/171 (2022.01)] 16 Claims
OG exemplary drawing
 
1. A method for training a neural network model, comprising:
generating an image of a mask;
generating a copy of an image from an original set of training data;
altering the copy to add the image of a mask to a face detected within the copy by generating a style transformation of the detected face using a generative adversarial network, including blending the altered copy to conform to an original three-dimensional structure of the detected face;
generating an augmented set of training data that includes the original set of training data and the altered copy; and
training a neural network model to recognize masked faces using the augmented set of training data.