公开(公告)号：US20250005824A1

公开(公告)日：2025-01-02

申请号：US18341982

申请日：2023-06-27

Applicant: ADOBE INC.

Inventor： Rishabh Jain ,  Mayur Hemani ,  Duygu Ceylan Aksit ,  Krishna Kumar Singh ,  Jingwan Lu ,  Mausoom Sarkar ,  Balaji Krishnamurthy

IPC: G06T11/60 ,  G06T3/00 ,  G06T7/11 ,  G06T11/00

Abstract: Systems and methods for image processing are described. One aspect of the systems and methods includes receiving a plurality of images comprising a first image depicting a first body part and a second image depicting a second body part and encoding, using a texture encoder, the first image and the second image to obtain a first texture embedding and a second texture embedding, respectively. Then, a composite image is generated using a generative decoder, the composite image depicting the first body part and the second body part based on the first texture embedding and the second texture embedding.

公开(公告)号：US20250005812A1

公开(公告)日：2025-01-02

申请号：US18215484

申请日：2023-06-28

Applicant: Adobe Inc.

Inventor： Rishabh Jain ,  Mayur Hemani ,  Mausoom Sarkar ,  Krishna Kumar Singh ,  Jingwan Lu ,  Duygu Ceylan Aksit ,  Balaji Krishnamurthy

IPC: G06T11/00 ,  G06T7/12 ,  G06T7/70

Abstract: In implementations of systems for human reposing based on multiple input views, a computing device implements a reposing system to receive input data describing: input digital images; pluralities of keypoints corresponding to the input digital images, the pluralities of keypoints representing poses of a person depicted in the input digital images; and a plurality of keypoints representing a target pose. The reposing system generates selection masks corresponding to the input digital images by processing the input data using a machine learning model. The selection masks represent likelihoods of spatial correspondence between pixels of an output digital image and portions of the input digital images. The reposing system generates the output digital image depicting the person in the target pose for display in a user interface based on the selection masks and the input data.

公开(公告)号：US20240428564A1

公开(公告)日：2024-12-26

申请号：US18213118

申请日：2023-06-22

Applicant: Adobe Inc.

Inventor： Rishabh Jain ,  Mayur Hemani ,  Mausoom Sarkar ,  Krishna Kumar Singh ,  Jingwan Lu ,  Duygu Ceylan Aksit ,  Balaji Krishnamurthy

IPC: G06V10/77 ,  G06T3/00 ,  G06T3/40

Abstract: In implementations of systems for generating images for human reposing, a computing device implements a reposing system to receive input data describing an input digital image depicting a person in a first pose, a first plurality of keypoints representing the first pose, and a second plurality of keypoints representing a second pose. The reposing system generates a mapping by processing the input data using a first machine learning model. The mapping indicates a plurality of first portions of the person in the second pose that are visible in the input digital image and a plurality of second portions of the person in the second pose that are invisible in the input digital image. The reposing system generates an output digital image depicting the person in the second pose by processing the mapping, the first plurality of keypoints, and the second plurality of keypoints using a second machine learning model.

公开(公告)号：US11861772B2

公开(公告)日：2024-01-02

申请号：US17678237

申请日：2022-02-23

Applicant: Adobe Inc.

Inventor： Ayush Chopra ,  Rishabh Jain ,  Mayur Hemani ,  Balaji Krishnamurthy

IPC: G06T11/60 ,  G06N3/045 ,  G06T7/11 ,  G06T7/70 ,  G06N3/044 ,  G06N3/08

CPC classification number: G06T11/60 ,  G06N3/045 ,  G06T7/11 ,  G06T7/70

Abstract: In implementations of systems for generating images for virtual try-on and pose transfer, a computing device implements a generator system to receive input data describing a first digital image that depicts a person in a pose and a second digital image that depicts a garment. Candidate appearance flow maps are computed that warp the garment based on the pose at different pixel-block sizes using a first machine learning model. The generator system generates a warped garment image by combining the candidate appearance flow maps as an aggregate per-pixel displacement map using a convolutional gated recurrent network. A conditional segment mask is predicted that segments portions of a geometry of the person using a second machine learning model. The generator system outputs a digital image that depicts the person in the pose wearing the garment based on the warped garment image and the conditional segmentation mask using a third machine learning model.

公开(公告)号：US20230267663A1

公开(公告)日：2023-08-24

申请号：US17678237

申请日：2022-02-23

Applicant: Adobe Inc.

Inventor： Ayush Chopra ,  Rishabh Jain ,  Mayur Hemani ,  Balaji Krishnamurthy

IPC: G06T11/60 ,  G06T7/70 ,  G06T7/11 ,  G06N3/04

CPC classification number: G06T11/60 ,  G06T7/70 ,  G06T7/11 ,  G06N3/0454

Abstract: In implementations of systems for generating images for virtual try-on and pose transfer, a computing device implements a generator system to receive input data describing a first digital image that depicts a person in a pose and a second digital image that depicts a garment. Candidate appearance flow maps are computed that warp the garment based on the pose at different pixel-block sizes using a first machine learning model. The generator system generates a warped garment image by combining the candidate appearance flow maps as an aggregate per-pixel displacement map using a convolutional gated recurrent network. A conditional segment mask is predicted that segments portions of a geometry of the person using a second machine learning model. The generator system outputs a digital image that depicts the person in the pose wearing the garment based on the warped garment image and the conditional segmentation mask using a third machine learning model.

公开(公告)号：US20240378912A1

公开(公告)日：2024-11-14

申请号：US18316617

申请日：2023-05-12

Applicant: Adobe Inc.

Inventor： Mausoom Sarkar ,  Nikitha S R ,  Mayur Hemani ,  Rishabh Jain ,  Balaji Krishnamurthy

IPC: G06V20/70 ,  G06T3/40 ,  G06T7/11 ,  G06V10/46 ,  G06V10/764 ,  G06V10/77 ,  G06V10/774 ,  G06V10/82 ,  G06V40/16

Abstract: This disclosure describes one or more implementations of systems, non-transitory computer-readable media, and methods that utilize a local implicit image function neural network to perform image segmentation with a continuous class label probability distribution. For example, the disclosed systems utilize a local-implicit-image-function (LIIF) network to learn a mapping from an image to its semantic label space. In some instances, the disclosed systems utilize an image encoder to generate an image vector representation from an image. Subsequently, in one or more implementations, the disclosed systems utilize the image vector representation with a LIIF network decoder that generates a continuous probability distribution in a label space for the image to create a semantic segmentation mask for the image. Moreover, in some embodiments, the disclosed systems utilize the LIIF-based segmentation network to generate segmentation masks at different resolutions without changes in an input resolution of the segmentation network.