公开(公告)号：US20200342634A1

公开(公告)日：2020-10-29

申请号：US16392968

申请日：2019-04-24

Applicant: Adobe Inc.

Inventor： Connelly Barnes ,  Sohrab Amirghodsi ,  Michal Lukac ,  Elya Shechtman ,  Ning Yu

IPC: G06T11/00 ,  G06T7/40

Abstract: Techniques are disclosed for neural network based interpolation of image textures. A methodology implementing the techniques according to an embodiment includes training a global encoder network to generate global latent vectors based on training texture images, and training a local encoder network to generate local latent tensors based on the training texture images. The method further includes interpolating between the global latent vectors associated with each set of training images, and interpolating between the local latent tensors associated with each set of training images. The method further includes training a decoder network to generate reconstructions of the training texture images and to generate an interpolated texture based on the interpolated global latent vectors and the interpolated local latent tensors. The training of the encoder and decoder networks is based on a minimization of a loss function of the reconstructions and a minimization of a loss function of the interpolated texture.

公开(公告)号：US10810721B2

公开(公告)日：2020-10-20

申请号：US15458826

申请日：2017-03-14

Applicant: Adobe Inc.

Inventor： Radomir Mech ,  Ning Yu ,  Xiaohui Shen ,  Zhe Lin

IPC: G06T7/00 ,  G06N3/08 ,  G06N3/04

Abstract: Digital image defect identification and correction techniques are described. In one example, a digital medium environment is configured to identify and correct a digital image defect through identification of a defect in a digital image using machine learning. The identification includes generating a plurality of defect type scores using a plurality of defect type identification models, as part of machine learning, for a plurality of different defect types and determining the digital image includes the defect based on the generated plurality of defect type scores. A correction is generated for the identified defect and the digital image is output as included the generated correction.

公开(公告)号：US10818043B1

公开(公告)日：2020-10-27

申请号：US16392968

申请日：2019-04-24

Applicant: Adobe Inc.

Inventor： Connelly Barnes ,  Sohrab Amirghodsi ,  Michal Lukac ,  Elya Shechtman ,  Ning Yu

IPC: G06T11/00 ,  G06T7/40

Abstract: An example method for neural network based interpolation of image textures includes training a global encoder network to generate global latent vectors based on training texture images, and training a local encoder network to generate local latent tensors based on the training texture images. The example method further includes interpolating between the global latent vectors associated with each set of training images, and interpolating between the local latent tensors associated with each set of training images. The example method further includes training a decoder network to generate reconstructions of the training texture images and to generate an interpolated texture based on the interpolated global latent vectors and the interpolated local latent tensors. The training of the encoder and decoder networks is based on a minimization of a loss function of the reconstructions and a minimization of a loss function of the interpolated texture.