公开(公告)号：US12020414B2

公开(公告)日：2024-06-25

申请号：US17819845

申请日：2022-08-15

Applicant: Adobe Inc.

Inventor： Scott Cohen ,  Zhe Lin ,  Mingyang Ling

IPC: G06T7/00 ,  G06F16/583 ,  G06F40/205 ,  G06T7/70 ,  G06T7/90 ,  G06T11/60

CPC classification number: G06T7/0002 ,  G06F16/5838 ,  G06F16/5854 ,  G06F40/205 ,  G06T7/70 ,  G06T7/90 ,  G06T11/60 ,  G06T2207/20084 ,  G06T2210/12

Abstract: The present disclosure relates to an object selection system that accurately detects and automatically selects target instances of user-requested objects (e.g., a query object instance) in a digital image. In one or more embodiments, the object selection system can analyze one or more user inputs to determine an optimal object attribute detection model from multiple specialized and generalized object attribute models. Additionally, the object selection system can utilize the selected object attribute model to detect and select one or more target instances of a query object in an image, where the image includes multiple instances of the query object.

公开(公告)号：US20240169628A1

公开(公告)日：2024-05-23

申请号：US18460150

申请日：2023-09-01

Applicant: Adobe Inc.

Inventor： Soo Ye Kim ,  Zhe Lin ,  Scott Cohen ,  Jianming Zhang ,  Luis Figueroa ,  Zhihong Ding

IPC: G06T11/60 ,  G06F3/0481 ,  G06F3/04845 ,  G06F3/0486 ,  G06T5/00 ,  G06T11/00

CPC classification number: G06T11/60 ,  G06F3/0481 ,  G06F3/04845 ,  G06F3/0486 ,  G06T5/002 ,  G06T5/005 ,  G06T11/001 ,  G06T2200/24 ,  G06T2207/20092 ,  G06T2207/20212

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that provides a graphical user interface experience to move objects and generate new shadows within a digital image scene. For instance, in one or more embodiments, the disclosed systems receive a digital image depicting a scene. The disclosed systems receive a selection to position an object in a first location within the scene. Further, the disclosed systems composite an image by placing the object at the first location within the scene of the digital image. Moreover, the disclosed systems generate a modified digital image having a shadow of the object where the shadow is consistent with the scene and provides the modified digital image to the client device.

公开(公告)号：US20240169624A1

公开(公告)日：2024-05-23

申请号：US18058538

申请日：2022-11-23

Applicant: Adobe Inc.

Inventor： Jonathan Brandt ,  Scott Cohen ,  Zhe Lin ,  Zhihong Ding ,  Darshan Prasad ,  Matthew Joss ,  Celso Gomes ,  Jianming Zhang ,  Olena Soroka ,  Klaas Stoeckmann ,  Michael Zimmermann ,  Thomas Muehrke

IPC: G06T11/60 ,  G06F3/04842 ,  G06F3/04845 ,  G06T11/40

CPC classification number: G06T11/60 ,  G06F3/04842 ,  G06F3/04845 ,  G06T11/40

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For instance, in one or more embodiments, the disclosed systems generate utilizing a segmentation neural network, an object mask for each object of a plurality of objects of a digital image. The disclosed systems detect a first user interaction with an object in the digital image displayed via a graphical user interface. The disclosed systems surface, via the graphical user interface, the object mask for the object in response to the first user interaction. The disclosed systems perform an object-aware modification of the digital image in response to a second user interaction with the object mask for the object.

公开(公告)号：US20240168617A1

公开(公告)日：2024-05-23

申请号：US18058622

申请日：2022-11-23

Applicant: Adobe Inc.

Inventor： Zhe Lin ,  Scott Cohen ,  Kushal Kafle

IPC: G06F3/04845 ,  G06F3/0482 ,  G06F3/04847 ,  G06F3/04886 ,  G06F40/166 ,  G06V10/26 ,  G06V20/70

CPC classification number: G06F3/04845 ,  G06F3/0482 ,  G06F3/04847 ,  G06F3/04886 ,  G06F40/166 ,  G06V10/26 ,  G06V20/70 ,  G06V10/82

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For instance, in one or more embodiments, the disclosed systems detect a selection of an object portrayed in a digital image displayed within a graphical user interface of a client device. The disclosed systems provide, for display within the graphical user interface in response to detecting the selection of the object, an interactive window displaying one or more attributes of the object. The disclosed systems receive, via the interactive window, a user interaction to change an attribute from the one or more attributes. The disclosed systems modify the digital image by changing the attribute of the object in accordance with the user interaction.

公开(公告)号：US20240153047A1

公开(公告)日：2024-05-09

申请号：US18404648

申请日：2024-01-04

Applicant: Adobe Inc.

Inventor： Kevin Gary Smith ,  Matthew Joss ,  Scott Cohen

IPC: G06T5/77 ,  G06F3/04845 ,  G06T5/70 ,  G06T7/11 ,  G06T7/194 ,  G06T7/70

CPC classification number: G06T5/77 ,  G06F3/04845 ,  G06T5/70 ,  G06T7/11 ,  G06T7/194 ,  G06T7/70 ,  G06T2200/24 ,  G06T2207/20021 ,  G06T2207/20084 ,  G06T2207/20092

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images using an intelligent user interface tool that determines the intent of a user interaction. For instance, in some embodiments, the disclosed systems receive, via a graphical user interface of a client device, a user interaction with a set of pixels within a digital image. The disclosed systems determine, based on the user interaction, a user intent for targeting one or more portions of the digital image for deletion, the one or more portions including an additional set of pixels that differs from the set of pixels. Based on the user intent, the disclosed systems modify the digital image to delete the one or more portions from the digital image

公开(公告)号：US20240135510A1

公开(公告)日：2024-04-25

申请号：US18190513

申请日：2023-03-27

Applicant: Adobe Inc.

Inventor： Qing Liu ,  Jianming Zhang ,  Krishna Kumar Singh ,  Scott Cohen ,  Zhe Lin

IPC: G06T5/00 ,  G06T7/11 ,  G06T7/40 ,  G06V10/25 ,  G06V10/764 ,  G06V10/82

CPC classification number: G06T5/005 ,  G06T7/11 ,  G06T7/40 ,  G06V10/25 ,  G06V10/764 ,  G06V10/82 ,  G06T2207/20104

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For example, in one or more embodiments the disclosed systems utilize generative machine learning models to create modified digital images portraying human subjects. In particular, the disclosed systems generate modified digital images by performing infill modifications to complete a digital image or human inpainting for portions of a digital image that portrays a human. Moreover, in some embodiments, the disclosed systems perform reposing of subjects portrayed within a digital image to generate modified digital images. In addition, the disclosed systems in some embodiments perform facial expression transfer and facial expression animations to generate modified digital images or animations.

公开(公告)号：US11900611B2

公开(公告)日：2024-02-13

申请号：US18147278

申请日：2022-12-28

Applicant: Adobe Inc.

Inventor： Yinan Zhao ,  Brian Price ,  Scott Cohen

IPC: G06T7/11 ,  G06T7/168 ,  G06T9/00 ,  G06T5/00 ,  G06T7/181

CPC classification number: G06T7/11 ,  G06T5/004 ,  G06T7/168 ,  G06T7/181 ,  G06T9/002 ,  G06T9/008

Abstract: The present disclosure relates to a class-agnostic object segmentation system that automatically detects, segments, and selects objects within digital images irrespective of object semantic classifications. For example, the object segmentation system utilizes a class-agnostic object segmentation neural network to segment each pixel in a digital image into an object mask. Further, in response to detecting a selection request of a target object, the object segmentation system utilizes a corresponding object mask to automatically select the target object within the digital image. In some implementations, the object segmentation system utilizes a class-agnostic object segmentation neural network to detect and automatically select a partial object in the digital image in response to a target object selection request.

公开(公告)号：US11886494B2

公开(公告)日：2024-01-30

申请号：US17929206

申请日：2022-09-01

Applicant: Adobe Inc.

Inventor： Walter Wei Tuh Chang ,  Khoi Pham ,  Scott Cohen ,  Zhe Lin ,  Zhihong Ding

IPC: G06F16/583 ,  G06F16/532 ,  G06F16/33 ,  G06T11/60 ,  G06F40/279 ,  G06F40/247 ,  G06N20/00 ,  G06F16/242 ,  G06F16/28 ,  G06F16/538 ,  G06F40/30 ,  G06F18/2431 ,  G06V10/82

CPC classification number: G06F16/5854 ,  G06F16/243 ,  G06F16/288 ,  G06F16/3344 ,  G06F16/532 ,  G06F16/538 ,  G06F18/2431 ,  G06F40/247 ,  G06F40/279 ,  G06F40/30 ,  G06N20/00 ,  G06T11/60 ,  G06V10/82

Abstract: The present disclosure relates to an object selection system that automatically detects and selects objects in a digital image based on natural language-based inputs. For instance, the object selection system can utilize natural language processing tools to detect objects and their corresponding relationships within natural language object selection queries. For example, the object selection system can determine alternative object terms for unrecognized objects in a natural language object selection query. As another example, the object selection system can determine multiple types of relationships between objects in a natural language object selection query and utilize different object relationship models to select the requested query object.

公开(公告)号：US20230351566A1

公开(公告)日：2023-11-02

申请号：US17660968

申请日：2022-04-27

Applicant: ADOBE INC.

Inventor： Sangryul Jeon ,  Zhifei Zhang ,  Zhe Lin ,  Scott Cohen ,  Zhihong Ding

IPC: G06T5/50 ,  G06V10/40 ,  G06V10/75 ,  G06V10/77 ,  G06V10/774 ,  G06V10/44

CPC classification number: G06T5/50 ,  G06V10/513 ,  G06V10/751 ,  G06V10/7715 ,  G06V10/774 ,  G06V10/454 ,  G06T2207/20221 ,  G06T2207/20081

Abstract: Systems and methods for image processing are configured. Embodiments of the present disclosure encode a content image and a style image using a machine learning model to obtain content features and style features, wherein the content image includes a first object having a first appearance attribute and the style image includes a second object having a second appearance attribute; align the content features and the style features to obtain a sparse correspondence map that indicates a correspondence between a sparse set of pixels of the content image and corresponding pixels of the style image; and generate a hybrid image based on the sparse correspondence map, wherein the hybrid image depicts the first object having the second appearance attribute.

公开(公告)号：US11797847B2

公开(公告)日：2023-10-24

申请号：US17387195

申请日：2021-07-28

Applicant: Adobe Inc.

Inventor： Scott Cohen ,  Zhe Lin ,  Mingyang Ling

IPC: G06N3/00 ,  G06N3/08 ,  G06T7/11 ,  G06T7/90 ,  G06F16/33 ,  G10L15/22 ,  G06F18/214 ,  G06N3/045 ,  G06V10/25 ,  G06V10/764 ,  G06V10/82

CPC classification number: G06N3/08 ,  G06F16/3344 ,  G06F18/214 ,  G06N3/045 ,  G06T7/11 ,  G06T7/90 ,  G06V10/25 ,  G06V10/764 ,  G06V10/82 ,  G10L15/22 ,  G06T2207/30252 ,  G10L2015/223

Abstract: The systems, methods, a non-transitory computer readable mediums relate to an object selection system that accurately detects and automatically selects user-requested objects (e.g., query objects) in a digital image. For example, the object selection system builds and utilizes an object selection pipeline to determine which object detection neural network to utilize to detect a query object based on analyzing the object class of the query object. In addition, the object selection system can add, update, or replace portions of the object selection pipeline to improve overall accuracy and efficiency of automatic object selection within an image.