公开(公告)号：US20190272451A1

公开(公告)日：2019-09-05

申请号：US16417115

申请日：2019-05-20

Applicant: Adobe Inc.

Inventor： Zhe Lin ,  Mai Long ,  Jonathan Brandt ,  Hailin Jin ,  Chen Fang

IPC: G06K9/66 ,  G06F16/532 ,  G06K9/72 ,  G06K9/62 ,  G06K9/46 ,  G06N3/08 ,  G06K9/52

Abstract: The present disclosure includes methods and systems for searching for digital visual media based on semantic and spatial information. In particular, one or more embodiments of the disclosed systems and methods identify digital visual media displaying targeted visual content in a targeted region based on a query term and a query area provide via a digital canvas. Specifically, the disclosed systems and methods can receive user input of a query term and a query area and provide the query term and query area to a query neural network to generate a query feature set. Moreover, the disclosed systems and methods can compare the query feature set to digital visual media feature sets. Further, based on the comparison, the disclosed systems and methods can identify digital visual media portraying targeted visual content corresponding to the query term within a targeted region corresponding to the query area.

公开(公告)号：US10319412B2

公开(公告)日：2019-06-11

申请号：US15353186

申请日：2016-11-16

Applicant: Adobe Inc.

Inventor： Zhihong Ding ,  Zhe Lin ,  Xiaohui Shen ,  Michael Kaplan ,  Jonathan Brandt

IPC: G11B27/11 ,  G06K9/32 ,  G06T11/60 ,  G11B27/031 ,  G06K9/00 ,  G06T7/00

Abstract: The present disclosure is directed toward systems and methods for tracking objects in videos. For example, one or more embodiments described herein utilize various tracking methods in combination with an image search index made up of still video frames indexed from a video. One or more embodiments described herein utilize a backward and forward tracking method that is anchored by one or more key frames in order to accurately track an object through the frames of a video, even when the video is long and may include challenging conditions.

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：US11775817B2

公开(公告)日：2023-10-03

申请号：US16549072

申请日：2019-08-23

Applicant: Adobe Inc.

Inventor： Jonathan Brandt ,  Chen Fang ,  Byungmoon Kim ,  Biao Jia

IPC: G06N3/08 ,  G09G5/37 ,  G06N3/04

CPC classification number: G06N3/08 ,  G06N3/04 ,  G09G5/37

Abstract: Some embodiments involve a reinforcement learning based framework for training a natural media agent to learn a rendering policy without human supervision or labeled datasets. The reinforcement learning based framework feeds the natural media agent a training dataset to implicitly learn the rendering policy by exploring a canvas and minimizing a loss function. Once trained, the natural media agent can be applied to any reference image to generate a series (or sequence) of continuous-valued primitive graphic actions, e.g., sequence of painting strokes, that when rendered by a synthetic rendering environment on a canvas, reproduce an identical or transformed version of the reference image subject to limitations of an action space and the learned rendering policy.