公开(公告)号：US20240185503A1

公开(公告)日：2024-06-06

申请号：US18439182

申请日：2024-02-12

Applicant: Adobe Inc.

Inventor： Theo Thonat ,  Xin Sun ,  Tamy Boubekeur ,  Nathan Carr ,  Francois Beaune

IPC: G06T15/04 ,  G06T15/06 ,  G06T17/20

CPC classification number: G06T15/04 ,  G06T15/06 ,  G06T17/20

Abstract: Aspects and features of the present disclosure provide a direct ray tracing operator with a low memory footprint for surfaces enriched with displacement maps. A graphics editing application can be used to manipulate displayed representations of a 3D object that include surfaces with displacement textures. The application creates an independent map of a displaced surface. The application ray-traces bounding volumes on the fly and uses the intersection of a query ray with a bounding volume to produce rendering information for a displaced surface. The rendering information can be used to generate displaced surfaces for various base surfaces without significant re-computation so that updated images can be rendered quickly, in real time or near real time.

公开(公告)号：US20240185393A1

公开(公告)日：2024-06-06

申请号：US18440248

申请日：2024-02-13

Applicant: Adobe Inc.

Inventor： He Zhang ,  Yifan Jiang ,  Yilin Wang ,  Jianming Zhang ,  Kalyan Sunkavalli ,  Sarah Kong ,  Su Chen ,  Sohrab Amirghodsi ,  Zhe Lin

IPC: G06T5/50 ,  G06N3/04 ,  G06N3/08 ,  G06T7/194 ,  G06T11/00 ,  G06T11/60

CPC classification number: G06T5/50 ,  G06N3/04 ,  G06N3/08 ,  G06T7/194 ,  G06T11/001 ,  G06T11/60 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20092 ,  G06T2207/20132 ,  G06T2207/20212

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately, efficiently, and flexibly generating harmonized digital images utilizing a self-supervised image harmonization neural network. In particular, the disclosed systems can implement, and learn parameters for, a self-supervised image harmonization neural network to extract content from one digital image (disentangled from its appearance) and appearance from another from another digital image (disentangled from its content). For example, the disclosed systems can utilize a dual data augmentation method to generate diverse triplets for parameter learning (including input digital images, reference digital images, and pseudo ground truth digital images), via cropping a digital image with perturbations using three-dimensional color lookup tables (“LUTs”). Additionally, the disclosed systems can utilize the self-supervised image harmonization neural network to generate harmonized digital images that depict content from one digital image having the appearance of another digital image.

公开(公告)号：US11995894B2

公开(公告)日：2024-05-28

申请号：US17017353

申请日：2020-09-10

Applicant: ADOBE INC.

Inventor： Seth Walker ,  Joy Oakyung Kim ,  Hijung Shin ,  Aseem Agarwala ,  Joel R. Brandt ,  Jovan Popović ,  Lubomira Dontcheva ,  Dingzeyu Li ,  Xue Bai

IPC: G06V20/40 ,  G06T7/10

CPC classification number: G06V20/49 ,  G06T7/10 ,  G06V20/41 ,  G06T2207/10016

Abstract: Embodiments are directed to techniques for interacting with a hierarchical video segmentation using a metadata panel with a composite list of video metadata. The composite list is segmented into selectable metadata segments at locations corresponding to boundaries of video segments defined by a hierarchical segmentation. In some embodiments, the finest level of a hierarchical segmentation identifies the smallest interaction unit of a video—semantically defined video segments of unequal duration called clip atoms, and higher levels cluster the clip atoms into coarser sets of video segments. One or more metadata segments can be selected in various ways, such as by clicking or tapping on a metadata segment or by performing a metadata search. When a metadata segment is selected, a corresponding video segment is emphasized on the video timeline, a playback cursor is moved to the first video frame of the video segment, and the first video frame is presented.

公开(公告)号：US11995158B2

公开(公告)日：2024-05-28

申请号：US17193251

申请日：2021-03-05

Applicant: Adobe Inc.

Inventor： Sachin Goyal ,  Harsh Agarwal ,  Cyril Thomas

IPC: G06F21/12 ,  G06F21/10 ,  G06F21/16 ,  G06F21/55 ,  G06F21/73

CPC classification number: G06F21/12 ,  G06F21/16 ,  G06F21/552 ,  G06F21/73 ,  G06F21/107

Abstract: Techniques are provided herein for tracking activation events associated with a given serial number and using the data from the activation events to autonomously determine whether the serial number has been leaked. Numerous different characteristic parameters of activation events collected over a given time period for a serial number can be tracked and stored in a database. A plurality of different input variables can be generated based on the characteristic parameter data, which create the inputs that are used by a trained neural network to determine the leakage probability. If the leakage probability is determined to be above a certain threshold, an alert of some kind can be generated to indicate that the serial number has been leaked.

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：US20240169553A1

公开(公告)日：2024-05-23

申请号：US18057436

申请日：2022-11-21

Applicant: Adobe Inc.

Inventor： Jae shin Yoon ,  Zhixin Shu ,  Yangtuanfeng Wang ,  Jingwan Lu ,  Jimei Yang ,  Duygu Ceylan Aksit

IPC: G06T7/20 ,  G06T13/40 ,  G06T15/04 ,  G06T17/00

CPC classification number: G06T7/20 ,  G06T13/40 ,  G06T15/04 ,  G06T17/00 ,  G06T2207/10016 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30244

Abstract: Techniques for modeling secondary motion based on three-dimensional models are described as implemented by a secondary motion modeling system, which is configured to receive a plurality of three-dimensional object models representing an object. Based on the three-dimensional object models, the secondary motion modeling system determines three-dimensional motion descriptors of a particular three-dimensional object model using one or more machine learning models. Based on the three-dimensional motion descriptors, the secondary motion modeling system models at least one feature subjected to secondary motion using the one or more machine learning models. The particular three-dimensional object model having the at least one feature is rendered by the secondary motion modeling system.

公开(公告)号：US20240169410A1

公开(公告)日：2024-05-23

申请号：US17980790

申请日：2022-11-04

Applicant: Adobe Inc.

Inventor： Handong Zhao ,  Zhankui He ,  Tong Yu ,  Fan Du ,  Sungchul Kim

IPC: G06Q30/06

CPC classification number: G06Q30/0631

Abstract: Techniques for predicting and recommending item bundles in a multi-round conversation to discover a target item bundle that would be accepted by a client. An example method includes receiving an input response in reply to a first item bundle that includes one or more items. A state model is updated to reflect the input response to the first item bundle. A machine-learning (ML) conversation module is applied to the state model to determine an action type as a follow-up to the input response to the first item bundle. Based on selection of a recommendation action as the action type, an ML bundling module is applied to the state model to generate a second item bundle different than the first item bundle. The second item bundle is then recommended.

公开(公告)号：US20240168625A1

公开(公告)日：2024-05-23

申请号：US18420444

申请日：2024-01-23

Applicant: Adobe Inc.

Inventor： Christopher Alan Tensmeyer ,  Rajiv Jain ,  Curtis Michael Wigington ,  Brian Lynn Price ,  Brian Lafayette Davis

IPC: G06F3/04883 ,  G06N3/045 ,  G06N3/08 ,  G06V10/44 ,  G06V10/82 ,  G06V30/226 ,  G06V30/228 ,  G06V30/32

CPC classification number: G06F3/04883 ,  G06N3/045 ,  G06N3/08 ,  G06V10/454 ,  G06V10/82 ,  G06V30/2264 ,  G06V30/2276 ,  G06V30/228 ,  G06V30/347

Abstract: Techniques are provided for generating a digital image of simulated handwriting using an encoder-decoder neural network trained on images of natural handwriting samples. The simulated handwriting image can be generated based on a style of a handwriting sample and a variable length coded text input. The style represents visually distinctive characteristics of the handwriting sample, such as the shape, size, slope, and spacing of the letters, characters, or other markings in the handwriting sample. The resulting simulated handwriting image can include the text input rendered in the style of the handwriting sample. The distinctive visual appearance of the letters or words in the simulated handwriting image mimics the visual appearance of the letters or words in the handwriting sample image, whether the letters or words in the simulated handwriting image are the same as in the handwriting sample image or different from those in the handwriting sample image.

公开(公告)号：US20240161529A1

公开(公告)日：2024-05-16

申请号：US18055752

申请日：2022-11-15

Applicant: Adobe Inc.

Inventor： Vlad Morariu ,  Puneet Mathur ,  Rajiv Jain ,  Ashutosh Mehra ,  Jiuxiang Gu ,  Franck Dernoncourt ,  Anandhavelu N ,  Quan Tran ,  Verena Kaynig-Fittkau ,  Nedim Lipka ,  Ani Nenkova

IPC: G06V30/413 ,  G06V10/82

CPC classification number: G06V30/413 ,  G06V10/82

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate a digital document hierarchy comprising layers of parent-child element relationships from the visual elements. For example, for a layer of the layers, the disclosed systems determine, from the visual elements, candidate parent visual elements and child visual elements. In addition, for the layer of the layers, the disclosed systems generate, from the feature embeddings utilizing a neural network, element classifications for the candidate parent visual elements and parent-child element link probabilities for the candidate parent visual elements and the child visual elements. Moreover, for the layer, the disclosed systems select parent visual elements from the candidate parent visual elements based on the parent-child element link probabilities. Further, the disclosed systems utilize the digital document hierarchy to generate an interactive digital document from the digital document image.

公开(公告)号：US20240161430A1

公开(公告)日：2024-05-16

申请号：US18054248

申请日：2022-11-10

Applicant: Adobe Inc.

Inventor： Sumit Dhingra ,  Siddhartha Chaudhuri ,  Vineet Batra

IPC: G06T19/20 ,  G06T7/13

CPC classification number: G06T19/20 ,  G06T7/13 ,  G06T2200/24 ,  G06T2207/20104 ,  G06T2207/20164 ,  G06T2219/2024

Abstract: This disclosure describes one or more implementations of systems, non-transitory computer-readable media, and methods that apply a resolution independent, vector-based decal on a 3D object. In one or more implementations, the disclosed systems apply piecewise non-linear transformation on an input decal vector geometry to align the decal with a surface of an underlying 3D object. To apply a vector-based decal on a 3D object, in certain embodiments, the disclosed systems parameterize a 3D mesh of the 3D object to create a mesh map. Moreover, in some instances, the disclosed systems determine intersections between edges of a decal geometry and edges of the mesh map to add vertices to the decal geometry at the intersections. Additionally, in some implementations, the disclosed systems lift and project vertices of the decal geometry into three dimensions to align the vertices with faces of the 3D mesh of the 3D object.