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1.发明授权公开(公告)号：US11157773B2
公开(公告)日：2021-10-26
申请号：US16802243
申请日：2020-02-26
Applicant: ADOBE INC.
Inventor： Cameron Smith , Yannick Hold-Geoffroy , Mariia Drozdova
Abstract: Images can be edited to include features similar to a different target image. An unconditional generative adversarial network (GAN) is employed to edit features of an initial image based on a constraint determined from a target image. The constraint used by the GAN is determined from keypoints or segmentation masks of the target image, and edits are made to features of the initial image based on keypoints or segmentation masks of the initial image corresponding to those of the constraint from the target image. The GAN modifies the initial image based on a loss function having a variable for the constraint. The result of this optimization process is a modified initial image having features similar to the target image subject to the constraint determined from the identified keypoints or segmentation masks.
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2.发明申请公开(公告)号：US20210264207A1
公开(公告)日：2021-08-26
申请号：US16802243
申请日：2020-02-26
Applicant: ADOBE INC.
Inventor： Cameron Smith , Yannick Hold-Geoffroy , Mariia Drozdova
Abstract: Images can be edited to include features similar to a different target image. An unconditional generative adversarial network (GAN) is employed to edit features of an initial image based on a constraint determined from a target image. The constraint used by the GAN is determined from keypoints or segmentation masks of the target image, and edits are made to features of the initial image based on keypoints or segmentation masks of the initial image corresponding to those of the constraint from the target image. The GAN modifies the initial image based on a loss function having a variable for the constraint. The result of this optimization process is a modified initial image having features similar to the target image subject to the constraint determined from the identified keypoints or segmentation masks.
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