公开(公告)号：US11748928B2

公开(公告)日：2023-09-05

申请号：US17094093

申请日：2020-11-10

申请人： Adobe Inc.

发明人： Yang Yang ,  Zhixin Shu ,  Shabnam Ghadar ,  Jingwan Lu ,  Jakub Fiser ,  Elya Schechtman ,  Cameron Y. Smith ,  Baldo Antonio Faieta ,  Alex Charles Filipkowski

IPC分类号： G06T11/60 ,  G06F21/62 ,  G06F16/56 ,  G06F16/532

CPC分类号： G06T11/60 ,  G06F16/532 ,  G06F16/56 ,  G06F21/6254 ,  G06T2200/24

摘要： Face anonymization techniques are described that overcome conventional challenges to generate an anonymized face. In one example, a digital object editing system is configured to generate an anonymized face based on a target face and a reference face. As part of this, the digital object editing system employs an encoder as part of machine learning to extract a target encoding of the target face image and a reference encoding of the reference face. The digital object editing system then generates a mixed encoding from the target and reference encodings. The mixed encoding is employed by a machine-learning model of the digital object editing system to generate a mixed face. An object replacement module is used by the digital object editing system to replace the target face in the target digital image with the mixed face.

公开(公告)号：US20230360299A1

公开(公告)日：2023-11-09

申请号：US18224916

申请日：2023-07-21

申请人： Adobe Inc.

发明人： Yang Yang ,  Zhixin Shu ,  Shabnam Ghadar ,  Jingwan Lu ,  Jakub Fiser ,  Elya Schechtman ,  Cameron Y. Smith ,  Baldo Antonio Faieta ,  Alex Charles Filipkowski

IPC分类号： G06T11/60 ,  G06F21/62 ,  G06F16/56 ,  G06F16/532

CPC分类号： G06T11/60 ,  G06F21/6254 ,  G06F16/56 ,  G06F16/532 ,  G06T2200/24

摘要： Face anonymization techniques are described that overcome conventional challenges to generate an anonymized face. In one example, a digital object editing system is configured to generate an anonymized face based on a target face and a reference face. As part of this, the digital object editing system employs an encoder as part of machine learning to extract a target encoding of the target face image and a reference encoding of the reference face. The digital object editing system then generates a mixed encoding from the target and reference encodings. The mixed encoding is employed by a machine-learning model of the digital object editing system to generate a mixed face. An object replacement module is used by the digital object editing system to replace the target face in the target digital image with the mixed face.

公开(公告)号：US20220148243A1

公开(公告)日：2022-05-12

申请号：US17094093

申请日：2020-11-10

申请人： Adobe Inc.

发明人： Yang Yang ,  Zhixin Shu ,  Shabnam Ghadar ,  Jingwan Lu ,  Jakub Fiser ,  Elya Schechtman ,  Cameron Y. Smith ,  Baldo Antonio Faieta ,  Alex Charles Filipkowski

IPC分类号： G06T11/60 ,  G06T9/00 ,  G06F3/0484 ,  G06F16/532 ,  G06F21/62 ,  G06F16/56 ,  G06N20/00

摘要： Face anonymization techniques are described that overcome conventional challenges to generate an anonymized face. In one example, a digital object editing system is configured to generate an anonymized face based on a target face and a reference face. As part of this, the digital object editing system employs an encoder as part of machine learning to extract a target encoding of the target face image and a reference encoding of the reference face. The digital object editing system then generates a mixed encoding from the target and reference encodings. The mixed encoding is employed by a machine-learning model of the digital object editing system to generate a mixed face. An object replacement module is used by the digital object editing system to replace the target face in the target digital image with the mixed face.