公开(公告)号：US20250166263A1

公开(公告)日：2025-05-22

申请号：US18947278

申请日：2024-11-14

Applicant: Samsung Electronics Co., Ltd.

Inventor： Hui LI

IPC: G06T11/60 ,  G06T3/40 ,  G06T5/50 ,  G06V10/80 ,  G06V40/16

Abstract: A processor-implemented method including obtaining a pyramid feature of an input face image, generating a first initial style feature corresponding to a highest level feature based on the highest level feature of the pyramid feature, and a latent code and noise of the input face image, generating a first style feature corresponding to each level feature based on an integrated feature corresponding to each level feature of the pyramid feature, the noise, and the latent code, and generating a high-quality face image of the input face image based on the first initial style feature and the first style feature corresponding to each level feature of the pyramid feature, the integrated feature corresponding to each level feature is generated based on each level feature, the first style feature corresponding to a higher level feature of each level feature, the latent code, and the noise and an integrated feature corresponding to the highest level feature of the pyramid feature is generated based on the highest level feature, the latent code, the noise, and the first initial style feature.

公开(公告)号：US20240161237A1

公开(公告)日：2024-05-16

申请号：US18497077

申请日：2023-10-30

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Seungju HAN ,  Hui LI

IPC: G06T3/40 ,  G06V10/77 ,  G06V10/80 ,  G06V10/82 ,  G06V40/16

CPC classification number: G06T3/4053 ,  G06T3/4046 ,  G06V10/7715 ,  G06V10/806 ,  G06V10/82 ,  G06V40/168

Abstract: An electronic device and a processor-implemented method with image processing are provided. The processor-implemented method comprises generating an initial image feature matrix of a face image based on a multi-level feature map of the face image; generating an initial face priori feature matrix of the face image based on a final level feature map of the multi-level feature map; and generating a super-resolution image of the face image and/or key point coordinates of the face image by using one or more encoders, based on the initial image feature matrix and the initial face priori feature matrix, wherein, when the one or more encoders are plural encoders, they are cascaded.

公开(公告)号：US20230154040A1

公开(公告)日：2023-05-18

申请号：US17987152

申请日：2022-11-15

Applicant: Samsung Electronics Co., Ltd.

Inventor： Zidong GUO ,  Jae-Joon HAN ,  Seon-Min RHEE ,  Seungju HAN ,  Hui LI

IPC: G06T7/73 ,  G06V10/766 ,  G06V10/82 ,  G06V10/774 ,  G06V10/77 ,  G06V40/16 ,  G06V10/776

CPC classification number: G06T7/73 ,  G06V10/766 ,  G06V10/82 ,  G06V10/774 ,  G06V10/7715 ,  G06V40/171 ,  G06V10/776 ,  G06V40/169 ,  G06T2207/30201 ,  G06T2207/20084 ,  G06T2207/20081

Abstract: A method and apparatus with landmark coordinate prediction are provided. The method includes generating a multi-stage feature map for landmarks of a face image through a staged convolutional network, generating an initial query matrix by fully connecting a last-stage feature map in the multi-stage feature map using a fully connected network, where a total number of feature elements in the initial query matrix is equal to a total number of predicted landmarks of the face image, generating a memory feature matrix by flattening and connecting the multi-stage feature map, generating the predicted landmark coordinates by inputting the memory feature matrix and the initial query matrix to a decoder network of plural cascaded decoder networks.

公开(公告)号：US20220301342A1

公开(公告)日：2022-09-22

申请号：US17695241

申请日：2022-03-15

Applicant: Samsung Electronics Co., Ltd.

Inventor： Hui LI ,  Jiguang XUE ,  Jaejoon HAN ,  Seon Min RHEE ,  Seungju HAN

IPC: G06V40/16 ,  G06T7/246

Abstract: A method with face recognition includes: determining a first global feature of a first face image and a first global feature of a second face image based on a local feature of the first face image and a local feature of the second face image, respectively; determining a final global feature of the first face image based on the first global feature of the first face image and a second global feature of the first face image; determining a final global feature of the second face image based on the first global feature and a second global feature of the second face image; and recognizing the first face image and the second face image based on the final global feature of the first face image and the final global feature of the second face image, wherein the second global feature of the first face image is determined based on the local feature of the first face image, and the second global feature of the second face image is determined based on the local feature of the second face image.