公开(公告)号：US11977829B2

公开(公告)日：2024-05-07

申请号：US17362031

申请日：2021-06-29

Applicant: Adobe Inc.

Inventor： Zhifei Zhang ,  Zhaowen Wang ,  Hailin Jin ,  Matthew Fisher

IPC: G06F40/109 ,  G06N3/045 ,  G06T11/20

CPC classification number: G06F40/109 ,  G06N3/045 ,  G06T11/203

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately and flexibly generating scalable and semantically editable font representations utilizing a machine learning approach. For example, the disclosed systems generate a font representation code from a glyph utilizing a particular neural network architecture. For example, the disclosed systems utilize a glyph appearance propagation model and perform an iterative process to generate a font representation code from an initial glyph. Additionally, using a glyph appearance propagation model, the disclosed systems automatically propagate the appearance of the initial glyph from the font representation code to generate additional glyphs corresponding to respective glyph labels. In some embodiments, the disclosed systems propagate edits or other changes in appearance of a glyph to other glyphs within a glyph set (e.g., to match the appearance of the edited glyph).

公开(公告)号：US11886793B2

公开(公告)日：2024-01-30

申请号：US17466679

申请日：2021-09-03

Applicant: ADOBE INC.

Inventor： Zhaowen Wang ,  Saeid Motiian ,  Baldo Faieta ,  Zegi Gu ,  Peter Evan O'Donovan ,  Alex Filipkowski ,  Jose Ignacio Echevarria Vallespi

IPC: G06F40/109 ,  G06F40/166 ,  G06F40/106 ,  G06F40/103

CPC classification number: G06F40/109 ,  G06F40/103 ,  G06F40/106 ,  G06F40/166

Abstract: Embodiments of the technology described herein, are an intelligent system that aims to expedite a text design process by providing text design predictions interactively. The system works with a typical text design scenario comprising a background image and one or more text strings as input. In the design scenario, the text string is to be placed on top of the background. The textual design agent may include a location recommendation model that recommends a location on the background image to place the text. The textual design agent may also include a font recommendation model, a size recommendation model, and a color recommendation model. The output of these four models may be combined to generate draft designs that are evaluated as a whole (combination of color, font, and size) for the best designs. The top designs may be output to the user.

公开(公告)号：US11823059B2

公开(公告)日：2023-11-21

申请号：US17377043

申请日：2021-07-15

Applicant: Adobe Inc. ,  The Regents of the University of California

Inventor： Chen Fang ,  Zhaowen Wang ,  Wangcheng Kang ,  Julian McAuley

IPC: G06N3/08 ,  G06F16/51 ,  G06N3/084

CPC classification number: G06N3/084 ,  G06F16/51

Abstract: The present disclosure relates to a fashion recommendation system that employs a task-guided learning framework to jointly train a visually-aware personalized preference ranking network. In addition, the fashion recommendation system employs implicit feedback and generated user-based triplets to learn variances in the user's fashion preferences for items with which the user has not yet interacted. In particular, the fashion recommendation system uses triplets generated from implicit user data to jointly train a Siamese convolutional neural network and a personalized ranking model, which together produce a user preference predictor that determines personalized fashion recommendations for a user.

公开(公告)号：US11710262B2

公开(公告)日：2023-07-25

申请号：US17675206

申请日：2022-02-18

Applicant: Adobe Inc.

Inventor： Nirmal Kumawat ,  Zhaowen Wang

IPC: G06T11/20 ,  G06F40/109 ,  G06F40/166 ,  G06V30/244

CPC classification number: G06T11/203 ,  G06F40/109 ,  G06F40/166 ,  G06V30/245

Abstract: Automatic font synthesis for modifying a local font to have an appearance that is visually similar to a source font is described. A font modification system receives an electronic document including the source font together with an indication of a font descriptor for the source font. The font descriptor includes information describing various font attributes for the source font, which define a visual appearance of the source font. Using the source font descriptor, the font modification system identifies a local font that is visually similar in appearance to the source font by comparing local font descriptors to the source font descriptor. A visually similar font is then synthesized by modifying glyph outlines of the local font to achieve the visual appearance defined by the source font descriptor. The synthesized font is then used to replace the source font and output in the electronic document at the computing device.

公开(公告)号：US11688190B2

公开(公告)日：2023-06-27

申请号：US17089865

申请日：2020-11-05

Applicant: ADOBE INC.

Inventor： Zhifei Zhang ,  Xingqian Xu ,  Zhaowen Wang ,  Brian Price

IPC: G06V30/148 ,  G06T7/194 ,  G06N20/00 ,  G06N3/04 ,  G06T11/60 ,  G06F18/214 ,  G06V30/10

CPC classification number: G06V30/153 ,  G06F18/214 ,  G06N3/04 ,  G06N20/00 ,  G06T7/194 ,  G06T11/60 ,  G06V30/10

Abstract: Systems and methods for text segmentation are described. Embodiments of the inventive concept are configured to receive an image including a foreground text portion and a background portion, classify each pixel of the image as foreground text or background using a neural network that refines a segmentation prediction using a key vector representing features of the foreground text portion, wherein the key vector is based on the segmentation prediction, and identify the foreground text portion based on the classification.

公开(公告)号：US11537518B2

公开(公告)日：2022-12-27

申请号：US15716050

申请日：2017-09-26

Applicant: Adobe Inc.

Inventor： Chih-Yao Hsieh ,  Zhaowen Wang

IPC: G06F12/0804 ,  G06F9/50 ,  G06F12/0846

Abstract: Constraining memory use for overlapping virtual memory operations is described. The memory use is constrained to prevent memory from exceeding an operational threshold, e.g., in relation to operations for modifying content. These operations are implemented according to algorithms having a plurality of instructions. Before the instructions are performed in relation to the content, virtual memory is allocated to the content data, which is then loaded into the virtual memory and is also partitioned into data portions. In the context of the described techniques, at least one of the instructions affects multiple portions of the content data loaded in virtual memory. When this occurs, the instruction is carried out, in part, by transferring the multiple portions of content data between the virtual memory and a memory such that a number of portions of the content data in the memory is constrained to the memory that is reserved for the operation.

公开(公告)号：US20220138483A1

公开(公告)日：2022-05-05

申请号：US17089865

申请日：2020-11-05

Applicant: ADOBE INC.

Inventor： Zhifei Zhang ,  Xingqian Xu ,  Zhaowen Wang ,  Brian Price

IPC: G06K9/34 ,  G06N20/00 ,  G06T7/194 ,  G06T11/60 ,  G06K9/62 ,  G06N3/04

Abstract: Systems and methods for text segmentation are described. Embodiments of the inventive concept are configured to receive an image including a foreground text portion and a background portion, classify each pixel of the image as foreground text or background using a neural network that refines a segmentation prediction using a key vector representing features of the foreground text portion, wherein the key vector is based on the segmentation prediction, and identify the foreground text portion based on the classification.

公开(公告)号：US11244207B2

公开(公告)日：2022-02-08

申请号：US17101778

申请日：2020-11-23

Applicant: Adobe Inc.

Inventor： Zhaowen Wang ,  Tianlang Chen ,  Ning Xu ,  Hailin Jin

IPC: G06K9/00 ,  G06K9/68 ,  G06K9/62 ,  G06K9/46 ,  G06F16/906 ,  G06N3/08 ,  G06F16/903 ,  G06F40/109

Abstract: The present disclosure relates to a tag-based font recognition system that utilizes a multi-learning framework to develop and improve tag-based font recognition using deep learning neural networks. In particular, the tag-based font recognition system jointly trains a font tag recognition neural network with an implicit font classification attention model to generate font tag probability vectors that are enhanced by implicit font classification information. Indeed, the font recognition system weights the hidden layers of the font tag recognition neural network with implicit font information to improve the accuracy and predictability of the font tag recognition neural network, which results in improved retrieval of fonts in response to a font tag query. Accordingly, using the enhanced tag probability vectors, the tag-based font recognition system can accurately identify and recommend one or more fonts in response to a font tag query.

公开(公告)号：US11232547B2

公开(公告)日：2022-01-25

申请号：US16930736

申请日：2020-07-16

Applicant: Adobe Inc.

Inventor： Chen Fang ,  Zhe Lin ,  Zhaowen Wang ,  Yulun Zhang ,  Yilin Wang ,  Jimei Yang

IPC: G06T11/00 ,  G06T5/50 ,  G06T3/40 ,  G06T7/11 ,  G06T3/00

Abstract: A style of a digital image is transferred to another digital image of arbitrary resolution. A high-resolution (HR) content image is segmented into several low-resolution (LR) patches. The resolution of a style image is matched to have the same resolution as the LR content image patches. Style transfer is then performed on a patch-by-patch basis using, for example, a pair of feature transforms—whitening and coloring. The patch-by-patch style transfer process is then repeated at several increasing resolutions, or scale levels, of both the content and style images. The results of the style transfer at each scale level are incorporated into successive scale levels up to and including the original HR scale. As a result, style transfer can be performed with images having arbitrary resolutions to produce visually pleasing results with good spatial consistency.

公开(公告)号：US11113599B2

公开(公告)日：2021-09-07

申请号：US15630604

申请日：2017-06-22

Applicant: Adobe Inc.

Inventor： Zhaowen Wang ,  Shuai Tang ,  Hailin Jin ,  Chen Fang

IPC: G06N3/08 ,  G06K9/00 ,  G06N20/00 ,  G06N3/04 ,  G06K9/62

Abstract: The present disclosure includes methods and systems for generating captions for digital images. In particular, the disclosed systems and methods can train an image encoder neural network and a sentence decoder neural network to generate a caption from an input digital image. For instance, in one or more embodiments, the disclosed systems and methods train an image encoder neural network (e.g., a character-level convolutional neural network) utilizing a semantic similarity constraint, training images, and training captions. Moreover, the disclosed systems and methods can train a sentence decoder neural network (e.g., a character-level recurrent neural network) utilizing training sentences and an adversarial classifier.