US 11,941,854 B2
Face image processing method and apparatus, image device, and storage medium
Wenyan Wu, Beijing (CN); Chen Qian, Beijing (CN); Keqiang Sun, Beijing (CN); Qianyi Wu, Beijing (CN); and Yuanyuan Xu, Beijing (CN)
Assigned to Beijing SenseTime Technology Development Co., Ltd., Beijing (CN)
Filed by Beijing SenseTime Technology Development Co., Ltd., Beijing (CN)
Filed on Mar. 16, 2021, as Appl. No. 17/203,171.
Application 17/203,171 is a continuation of application No. PCT/CN2020/087231, filed on Apr. 27, 2020.
Claims priority of application No. 201910804179.9 (CN), filed on Aug. 28, 2019.
Prior Publication US 2021/0201458 A1, Jul. 1, 2021
Int. Cl. G06T 9/00 (2006.01); G06N 3/02 (2006.01); G06T 3/00 (2006.01); G06T 5/50 (2006.01); G06T 7/40 (2017.01); G06T 7/60 (2017.01); G06V 10/75 (2022.01); G06V 40/16 (2022.01)
CPC G06T 9/002 (2013.01) [G06N 3/02 (2013.01); G06T 3/00 (2013.01); G06T 5/50 (2013.01); G06T 7/40 (2013.01); G06T 7/60 (2013.01); G06V 10/755 (2022.01); G06V 40/171 (2022.01); G06T 2207/20084 (2013.01); G06T 2207/20221 (2013.01); G06T 2207/30201 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A method for face image processing, comprising:
acquiring first-key-point information of a first face image;
performing position transformation on the first-key-point information to obtain second-key-point information conforming to a second facial geometric attribute, the second facial geometric attribute being different from a first facial geometric attribute corresponding to the first-key-point information; and
performing facial texture coding processing by utilizing a neural network and the second-key-point information to obtain a second face image,
wherein performing facial texture coding processing by utilizing the neural network and the second-key-point information to obtain the second face image comprises:
generating a mask map of a target face based on the second-key-point information, values of pixels in a face image area in the mask map being a first predetermined value, values of pixels outside the face image area being a second predetermined value, and the face image area being defined by each second key point describing a facial contour;
fusing the mask map and the first face image to generate a fused face image, the face image area in the first face image being reserved in the fused face image;
generating a contour map of geometric attributes of the target face based on the second-key-point information, values of pixels on a contour line of each part in the contour map being a third predetermined value, values of pixels other than the pixels on the contour line of each part being a fourth predetermined value, and the contour line of each part being defined by second key points describing each face part; and
inputting the fused face image and the contour map into the neural network for facial texture coding to obtain the second face image.