公开(公告)号：US12254594B2

公开(公告)日：2025-03-18

申请号：US17657691

申请日：2022-04-01

Applicant: Adobe Inc.

Inventor： Hui Qu ,  Jingwan Lu ,  Saeid Motiian ,  Shabnam Ghadar ,  Wei-An Lin ,  Elya Shechtman

IPC: G06T5/50 ,  G06N3/04 ,  G06N3/045 ,  G06T7/11

Abstract: Methods, systems, and non-transitory computer readable media are disclosed for intelligently enhancing details in edited images. The disclosed system iteratively updates residual detail latent code for segments in edited images where detail has been lost through the editing process. More particularly, the disclosed system enhances an edited segment in an edited image based on details in a detailed segment of an image. Additionally, the disclosed system may utilize a detail neural network encoder to project the detailed segment and a corresponding segment of the edited image into a residual detail latent code. In some embodiments, the disclosed system generates a refined edited image based on the residual detail latent code and a latent vector of the edited image.

公开(公告)号：US12093308B2

公开(公告)日：2024-09-17

申请号：US17453595

申请日：2021-11-04

Applicant: ADOBE INC.

Inventor： Baldo Faieta ,  Ajinkya Gorakhnath Kale ,  Pranav Vineet Aggarwal ,  Naveen Marri ,  Saeid Motiian ,  Tracy Holloway King ,  Alex Filipkowski ,  Shabnam Ghadar

IPC: G06F16/583 ,  G06F16/535 ,  G06F16/538 ,  G06F16/58 ,  G06F40/295 ,  G06N3/08

CPC classification number: G06F16/5838 ,  G06F16/535 ,  G06F16/538 ,  G06F16/5866 ,  G06F40/295 ,  G06N3/08

Abstract: Systems and methods for image retrieval are described. Embodiments of the present disclosure receive a search query from a user; extract an entity and a color phrase describing the entity from the search query; generate an entity color embedding in a color embedding space from the color phrase using a multi-modal color encoder; identify an image in a database based on metadata for the image including an object label corresponding to the extracted entity and an object color embedding in the color embedding space corresponding to the object label; and provide image information for the image to the user based on the metadata.

公开(公告)号：US20240037805A1

公开(公告)日：2024-02-01

申请号：US17813987

申请日：2022-07-21

Applicant: ADOBE INC.

Inventor： Saeid Motiian ,  Wei-An Lin ,  Shabnam Ghadar

IPC: G06T11/00 ,  G06V40/16

CPC classification number: G06T11/00 ,  G06V40/168 ,  G06T2200/24

Abstract: Systems and methods for facial image generation are described. One aspect of the systems and methods includes receiving an image depicting a face, wherein the face has an identity non-related attribute and a first identity-related attribute; encoding the image to obtain an identity non-related attribute vector in an identity non-related attribute vector space, wherein the identity non-related attribute vector represents the identity non-related attribute; selecting an identity-related vector from an identity-related vector space, wherein the identity-related vector represents a second identity-related attribute different from the first identity-related attribute; generating a modified latent vector in a latent vector space based on the identity non-related attribute vector and the identity-related vector; and generating a modified image based on the modified latent vector, wherein the modified image depicts a face that has the identity non-related attribute and the second identity-related attribute.

公开(公告)号：US11854119B2

公开(公告)日：2023-12-26

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: G06N3/08 ,  G06T7/90 ,  G06N3/045 ,  G06T11/00

CPC classification number: G06T11/001 ,  G06N3/045 ,  G06N3/08 ,  G06T7/90

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：US11823490B2

公开(公告)日：2023-11-21

申请号：US17341778

申请日：2021-06-08

Applicant: ADOBE INC.

Inventor： Ratheesh Kalarot ,  Siavash Khodadadeh ,  Baldo Faieta ,  Shabnam Ghadar ,  Saeid Motiian ,  Wei-An Lin ,  Zhe Lin

IPC: G06V40/16 ,  G06N3/084 ,  G06T11/60 ,  G06N3/045

CPC classification number: G06V40/169 ,  G06N3/045 ,  G06N3/084 ,  G06T11/60

Abstract: Systems and methods for image processing are described. One or more embodiments of the present disclosure identify a latent vector representing an image of a face, identify a target attribute vector representing a target attribute for the image, generate a modified latent vector using a mapping network that converts the latent vector and the target attribute vector into a hidden representation having fewer dimensions than the latent vector, wherein the modified latent vector is generated based on the hidden representation, and generate a modified image based on the modified latent vector, wherein the modified image represents the face with the target attribute.

公开(公告)号：US20230316606A1

公开(公告)日：2023-10-05

申请号：US17655739

申请日：2022-03-21

Applicant: Adobe Inc.

Inventor： Hui Qu ,  Baldo Faieta ,  Cameron Smith ,  Elya Shechtman ,  Jingwan Lu ,  Ratheesh Kalarot ,  Richard Zhang ,  Saeid Motiian ,  Shabnam Ghadar ,  Wei-An Lin

IPC: G06N3/04 ,  G06T11/60

CPC classification number: G06T11/60 ,  G06N3/0454

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for latent-based editing of digital images using a generative neural network. In particular, in one or more embodiments, the disclosed systems perform latent-based editing of a digital image by mapping a feature tensor and a set of style vectors for the digital image into a joint feature style space. In one or more implementations, the disclosed systems apply a joint feature style perturbation and/or modification vectors within the joint feature style space to determine modified style vectors and a modified feature tensor. Moreover, in one or more embodiments the disclosed systems generate a modified digital image utilizing a generative neural network from the modified style vectors and the modified feature tensor.

公开(公告)号：US20230316474A1

公开(公告)日：2023-10-05

申请号：US17657691

申请日：2022-04-01

Applicant: Adobe Inc.

Inventor： Hui Qu ,  Jingwan Lu ,  Saeid Motiian ,  Shabnam Ghadar ,  Wei-An Lin ,  Elya Shechtman

IPC: G06T5/50 ,  G06T7/11 ,  G06N3/04

CPC classification number: G06T5/50 ,  G06T7/11 ,  G06N3/0454 ,  G06T2207/20172 ,  G06T2207/20084

Abstract: Methods, systems, and non-transitory computer readable media are disclosed for intelligently enhancing details in edited images. The disclosed system iteratively updates residual detail latent code for segments in edited images where detail has been lost through the editing process. More particularly, the disclosed system enhances an edited segment in an edited image based on details in a detailed segment of an image. Additionally, the disclosed system may utilize a detail neural network encoder to project the detailed segment and a corresponding segment of the edited image into a residual detail latent code. In some embodiments, the disclosed system generates a refined edited image based on the residual detail latent code and a latent vector of the edited image.

公开(公告)号：US11775578B2

公开(公告)日：2023-10-03

申请号：US17398317

申请日：2021-08-10

Applicant: Adobe Inc.

Inventor： Pranav Vineet Aggarwal ,  Zhe Lin ,  Baldo Antonio Faieta ,  Saeid Motiian

IPC: G06K9/62 ,  G06K9/72 ,  G06F16/535 ,  G06N20/00 ,  G06V30/262 ,  G06F18/40 ,  G06F18/214 ,  G06V30/19 ,  G06V10/82 ,  G06V10/94 ,  G06F3/0482

CPC classification number: G06F16/535 ,  G06F18/2148 ,  G06F18/40 ,  G06N20/00 ,  G06V10/82 ,  G06V10/945 ,  G06V30/1916 ,  G06V30/19147 ,  G06V30/19173 ,  G06V30/274 ,  G06F3/0482

Abstract: Text-to-visual machine learning embedding techniques are described that overcome the challenges of conventional techniques in a variety of ways. These techniques include use of query-based training data which may expand availability and types of training data usable to train a model. Generation of negative digital image samples is also described that may increase accuracy in training the model using machine learning. A loss function is also described that also supports increased accuracy and computational efficiency by losses separately, e.g., between positive or negative sample embeddings a text embedding.

公开(公告)号：US11709885B2

公开(公告)日：2023-07-25

申请号：US17025041

申请日：2020-09-18

Applicant: Adobe Inc.

Inventor： John Collomosse ,  Zhe Lin ,  Saeid Motiian ,  Hailin Jin ,  Baldo Faieta ,  Alex Filipkowski

IPC: G06T7/00 ,  G06F16/583 ,  G06F16/532 ,  G06N3/08 ,  G06F16/535 ,  G06V10/82 ,  G06V20/30

CPC classification number: G06F16/5854 ,  G06F16/532 ,  G06F16/535 ,  G06F16/5838 ,  G06N3/08 ,  G06V10/82 ,  G06V20/30

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately and flexibly identifying digital images with similar style to a query digital image using fine-grain style determination via weakly supervised style extraction neural networks. For example, the disclosed systems can extract a style embedding from a query digital image using a style extraction neural network such as a novel two-branch autoencoder architecture or a weakly supervised discriminative neural network. The disclosed systems can generate a combined style embedding by combining complementary style embeddings from different style extraction neural networks. Moreover, the disclosed systems can search a repository of digital images to identify digital images with similar style to the query digital image. The disclosed systems can also learn parameters for one or more style extraction neural network through weakly supervised training without a specifically labeled style ontology for sample digital images.

公开(公告)号：US11663264B2

公开(公告)日：2023-05-30

申请号：US16785410

申请日：2020-02-07

Applicant: Adobe Inc.

Inventor： Pramod Srinivasan ,  Zhe Lin ,  Samarth Gulati ,  Saeid Motiian ,  Midhun Harikumar ,  Baldo Antonio Faieta ,  Alex C. Filipkowski

IPC: G06F16/532 ,  G06F16/583 ,  G06F16/538 ,  G06F40/30 ,  G06F16/51 ,  G06F16/54

CPC classification number: G06F16/532 ,  G06F16/51 ,  G06F16/538 ,  G06F16/54 ,  G06F16/583 ,  G06F40/30

Abstract: Keyword localization digital image search techniques are described. These techniques support an ability to indicate “where” a corresponding keyword is to be expressed with respect to a layout in a respective digital image resulting from a search query. The search query may also include an indication of a size of the keyword as expressed in the digital image, a number of instances of the keyword, and so forth. Additionally, the techniques and systems as described herein support real time search through use of keyword signatures.