公开(公告)号：US20240070884A1

公开(公告)日：2024-02-29

申请号：US17896574

申请日：2022-08-26

Applicant: ADOBE INC.

Inventor： Taesung PARK ,  Sylvain PARIS ,  Richard ZHANG ,  Elya SHECHTMAN

IPC: G06T7/40 ,  G06T5/50

CPC classification number: G06T7/40 ,  G06T5/50 ,  G06T2207/10028

Abstract: An image processing system uses a depth-conditioned autoencoder to generate a modified image from an input image such that the modified image maintains an overall structure from the input image while modifying textural features. An encoder of the depth-conditioned autoencoder extracts a structure latent code from an input image and depth information for the input image. A generator of the depth-conditioned autoencoder generates a modified image using the structure latent code and a texture latent code. The modified image generated by the depth-conditioned autoencoder includes the structural features from the input image while incorporating textural features of the texture latent code. In some aspects, the autoencoder is depth-conditioned during training by augmenting training images with depth information. The autoencoder is trained to preserve the depth information when generating images.

公开(公告)号：US20220237830A1

公开(公告)日：2022-07-28

申请号：US17155570

申请日：2021-01-22

Applicant: Adobe Inc.

Inventor： Siavash KHODADADEH ,  Zhe LIN ,  Shabnam GHADAR ,  Saeid MOTIIAN ,  Richard ZHANG ,  Ratheesh KALAROT ,  Baldo FAIETA

IPC: G06T11/00 ,  G06T7/90 ,  G06N3/04 ,  G06N3/08

Abstract: Embodiments are disclosed for automatic object re-colorization in images. In some embodiments, a method of automatic object re-colorization includes receiving a request to recolor an object in an image, the request including an object identifier and a color identifier, identifying an object in the image associated with the object identifier, generating a mask corresponding to the object in the image, providing the image, the mask, and the color identifier to a color transformer network, the color transformer network trained to recolor objects in input images, and generating, by the color transformer network, a recolored image, wherein the object in the recolored image has been recolored to a color corresponding to the color identifier

公开(公告)号：US20220156522A1

公开(公告)日：2022-05-19

申请号：US16951782

申请日：2020-11-18

Applicant: Adobe Inc.

Inventor： Elya SHECHTMAN ,  William PEEBLES ,  Richard ZHANG ,  Jun-Yan ZHU ,  Alyosha EFROS

IPC: G06K9/62 ,  G06T3/00 ,  G06N3/04 ,  G06N3/08

Abstract: Embodiments are disclosed for generative image congealing which provides an unsupervised learning technique that learns transformations of real data to improve the image quality of GANs trained using that image data. In particular, in one or more embodiments, the disclosed systems and methods comprise generating, by a spatial transformer network, an aligned real image for a real image from an unaligned real dataset, providing, by the spatial transformer network, the aligned real image to an adversarial discrimination network to determine if the aligned real image resembles aligned synthetic images generated by a generator network, and training, by a training manager, the spatial transformer network to learn updated transformations based on the determination of the adversarial discrimination network.