公开(公告)号：US12217395B2

公开(公告)日：2025-02-04

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

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：US12118752B2

公开(公告)日：2024-10-15

申请号：US17658799

申请日：2022-04-11

Applicant: Adobe Inc.

Inventor： Zhihong Ding ,  Scott Cohen ,  Zhe Lin ,  Mingyang Ling

IPC: G06T7/90 ,  G06F18/22 ,  G06F18/24 ,  G06N3/02 ,  G06V10/56 ,  G06V20/20

CPC classification number: G06T7/90 ,  G06F18/22 ,  G06F18/24 ,  G06N3/02 ,  G06V10/56 ,  G06V20/20 ,  G06T2207/10024 ,  G06T2207/20084

Abstract: The present disclosure relates to a color classification system that accurately classifies objects in digital images based on color. In particular, in one or more embodiments, the color classification system utilizes a multidimensional color space and one or more color mappings to match objects to colors. Indeed, the color classification system can accurately and efficiently detect the color of an object utilizing one or more color similarity regions generated in the multidimensional color space.

公开(公告)号：US20240169631A1

公开(公告)日：2024-05-23

申请号：US18532485

申请日：2023-12-07

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 modify digital images via scene-based editing to remove a shadow for an object. For instance, in one or more embodiments, the disclosed systems receive a digital image depicting a scene. The disclosed systems access a shadow mask of the shadow in a first location. Further, the disclosed systems generate the modified digital image without the shadow by generating a fill for the first location that preserves a visible location of the first location. Moreover, the disclosed systems generate the digital image without the shadow for the object by combining the fill with the digital image.

公开(公告)号：US20240161344A1

公开(公告)日：2024-05-16

申请号：US18053111

申请日：2022-11-07

Applicant: Adobe Inc. ,  York University

Inventor： Hoang M. Le ,  Michael S. Brown ,  Brian Price ,  Scott Cohen

IPC: G06T7/90 ,  G06T11/00

CPC classification number: G06T7/90 ,  G06T11/001 ,  G06T2207/10024 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30168

Abstract: Systems, methods, and non-transitory computer-readable media embed a trained neural network within a digital image. For instance, in one or more embodiments, the systems identify out-of-gamut pixel values of a digital image in a first gamut, where the digital image is converted to the first gamut from a second gamut. Furthermore, the systems determine target pixel values of a target version of the digital image in the first gamut that correspond to the out-of-gamut pixel values. The systems train a neural network to predict the target pixel values in the first gamut based on the out-of-gamut pixel values. The systems embed the neural network within the digital image in the second gamut to allow for extraction of the embedded neural network from the digital image to restore the digital image to a larger gamut digital image.

公开(公告)号：US11972569B2

公开(公告)日：2024-04-30

申请号：US17158527

申请日：2021-01-26

Applicant: Adobe Inc.

Inventor： Brian Price ,  David Hart ,  Zhihong Ding ,  Scott Cohen

IPC: G06T7/11 ,  G06T3/40 ,  G06T3/4046 ,  G06T7/174 ,  G06T7/187

CPC classification number: G06T7/11 ,  G06T3/4046 ,  G06T7/174 ,  G06T7/187

Abstract: The present disclosure relates to a multi-model object segmentation system that provides a multi-model object segmentation framework for automatically segmenting objects in digital images. In one or more implementations, the multi-model object segmentation system utilizes different types of object segmentation models to determine a comprehensive set of object masks for a digital image. In various implementations, the multi-model object segmentation system further improves and refines object masks in the set of object masks utilizing specialized object segmentation models, which results in more improved accuracy and precision with respect to object selection within the digital image. Further, in some implementations, the multi-model object segmentation system generates object masks for portions of a digital image otherwise not captured by various object segmentation models.

公开(公告)号：US20240135561A1

公开(公告)日：2024-04-25

申请号：US18320714

申请日：2023-05-19

Applicant: Adobe Inc.

Inventor： Zhihong Ding ,  Scott Cohen ,  Matthew Joss ,  Jianming Zhang ,  Darshan Prasad ,  Celso Gomes ,  Jonathan Brandt

IPC: G06T7/50 ,  G06T5/00 ,  G06V10/26

CPC classification number: G06T7/50 ,  G06T5/005 ,  G06V10/26 ,  G06T2207/20084

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that implement depth-aware object move operations for digital image editing. For instance, in some embodiments, the disclosed systems determine a first object depth for a first object portrayed within a digital image and a second object depth for a second object portrayed within the digital image. Additionally, the disclosed systems move the first object to create an overlap area between the first object and the second object within the digital image. Based on the first object depth and the second object depth, the disclosed systems modify the digital image to occlude the first object or the second object within the overlap area.

公开(公告)号：US20240135509A1

公开(公告)日：2024-04-25

申请号：US18190500

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 ,  G06T11/60 ,  G06V10/764 ,  G06V10/82 ,  G06V20/70

CPC classification number: G06T5/005 ,  G06T5/002 ,  G06T7/11 ,  G06T11/60 ,  G06V10/764 ,  G06V10/82 ,  G06V20/70 ,  G06T2200/24 ,  G06T2207/20021 ,  G06T2207/20084

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：US20240127411A1

公开(公告)日：2024-04-18

申请号：US17937706

申请日：2022-10-03

Applicant: Adobe Inc.

Inventor： Zhe Lin ,  Haitian Zheng ,  Elya Shechtman ,  Jianming Zhang ,  Jingwan Lu ,  Ning Xu ,  Qing Liu ,  Scott Cohen ,  Sohrab Amirghodsi

IPC: G06T5/00 ,  G06T7/11

CPC classification number: G06T5/005 ,  G06T7/11 ,  G06T2200/24 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for panoptically guiding digital image inpainting utilizing a panoptic inpainting neural network. In some embodiments, the disclosed systems utilize a panoptic inpainting neural network to generate an inpainted digital image according to panoptic segmentation map that defines pixel regions corresponding to different panoptic labels. In some cases, the disclosed systems train a neural network utilizing a semantic discriminator that facilitates generation of digital images that are realistic while also conforming to a semantic segmentation. The disclosed systems generate and provide a panoptic inpainting interface to facilitate user interaction for inpainting digital images. In certain embodiments, the disclosed systems iteratively update an inpainted digital image based on changes to a panoptic segmentation map.

公开(公告)号：US20240127410A1

公开(公告)日：2024-04-18

申请号：US17937695

申请日：2022-10-03

Applicant: Adobe Inc.

Inventor： Zhe Lin ,  Haitian Zheng ,  Elya Shechtman ,  Jianming Zhang ,  Jingwan Lu ,  Ning Xu ,  Qing Liu ,  Scott Cohen ,  Sohrab Amirghodsi

IPC: G06T5/00 ,  G06T7/11

CPC classification number: G06T5/005 ,  G06T7/11 ,  G06T2207/20084

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for panoptically guiding digital image inpainting utilizing a panoptic inpainting neural network. In some embodiments, the disclosed systems utilize a panoptic inpainting neural network to generate an inpainted digital image according to panoptic segmentation map that defines pixel regions corresponding to different panoptic labels. In some cases, the disclosed systems train a neural network utilizing a semantic discriminator that facilitates generation of digital images that are realistic while also conforming to a semantic segmentation. The disclosed systems generate and provide a panoptic inpainting interface to facilitate user interaction for inpainting digital images. In certain embodiments, the disclosed systems iteratively update an inpainted digital image based on changes to a panoptic segmentation map.

公开(公告)号：US11880977B2

公开(公告)日：2024-01-23

申请号：US17313158

申请日：2021-05-06

Applicant: Adobe Inc.

Inventor： Brian Lynn Price ,  Scott Cohen ,  Marco Forte ,  Ning Xu

IPC: G06T7/11 ,  G06T7/136 ,  G06T7/194 ,  G06T7/90 ,  G06T3/40 ,  G06N3/088 ,  G06N3/045 ,  G06N3/02 ,  G06N20/00

CPC classification number: G06T7/11 ,  G06N3/045 ,  G06N3/088 ,  G06T3/40 ,  G06T7/136 ,  G06T7/194 ,  G06T7/90 ,  G06N3/02 ,  G06N20/00 ,  G06T2207/10024 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20096 ,  G06T2207/20104

Abstract: Techniques are disclosed for deep neural network (DNN) based interactive image matting. A methodology implementing the techniques according to an embodiment includes generating, by the DNN, an alpha matte associated with an image, based on user-specified foreground region locations in the image. The method further includes applying a first DNN subnetwork to the image, the first subnetwork trained to generate a binary mask based on the user input, the binary mask designating pixels of the image as background or foreground. The method further includes applying a second DNN subnetwork to the generated binary mask, the second subnetwork trained to generate a trimap based on the user input, the trimap designating pixels of the image as background, foreground, or uncertain status. The method further includes applying a third DNN subnetwork to the generated trimap, the third subnetwork trained to generate the alpha matte based on the user input.