公开(公告)号：US20230252071A1

公开(公告)日：2023-08-10

申请号：US18302201

申请日：2023-04-18

Applicant: Adobe Inc.

Inventor： Pramod Srinivasan ,  Zhe Lin ,  Samarth Gulati ,  Saeid Motiian ,  Midhun Harikumar ,  Baldo Antonio Faieta ,  Alex C. Filipkowski

IPC: G06F16/532 ,  G06F16/538 ,  G06F40/30 ,  G06F16/583 ,  G06F16/51 ,  G06F16/54

CPC classification number: G06F16/532 ,  G06F16/51 ,  G06F16/54 ,  G06F16/538 ,  G06F16/583 ,  G06F40/30

Abstract: Keyword localization digital image search techniques are described. These techniques support an ability to indicate “where” a corresponding keyword is to be expressed with respect to a layout in a respective digital image resulting from a search query. The search query may also include an indication of a size of the keyword as expressed in the digital image, a number of instances of the keyword, and so forth. Additionally, the techniques and systems as described herein support real time search through use of keyword signatures.

公开(公告)号：US11711581B2

公开(公告)日：2023-07-25

申请号：US17200691

申请日：2021-03-12

Applicant: Adobe Inc.

Inventor： Handong Zhao ,  Zhankui He ,  Zhe Lin ,  Zhaowen Wang ,  Ajinkya Gorakhnath Kale

IPC: G06Q30/00 ,  H04N21/466 ,  G06N3/08 ,  H04N21/45 ,  H04N21/4722 ,  G06Q30/0282 ,  G06Q30/0601

CPC classification number: H04N21/4666 ,  G06N3/08 ,  G06Q30/0282 ,  G06Q30/0631 ,  H04N21/4532 ,  H04N21/4667 ,  H04N21/4722

Abstract: A multimodal recommendation identification system analyzes data describing a sequence of past content item interactions to generate a recommendation for a content item for a user. An indication of the recommended content item is provided to a website hosting system or recommendation system so that the recommended content item is displayed or otherwise presented to the user. The multimodal recommendation identification system identifies a content item to recommend to the user by generating an encoding that encodes identifiers of the sequence of content items the user has interacted with and generating encodings that encode multimodal information for content items in the sequence of content items the user has interacted with. An aggregated information encoding for a user based on these encodings and a system analyzes the content item sequence encoding and interaction between the content item sequence encoding and the multiple modality encodings to generate the aggregated information encoding.

公开(公告)号：US20230206462A1

公开(公告)日：2023-06-29

申请号：US18175481

申请日：2023-02-27

Applicant: Adobe Inc.

Inventor： Qihang Yu ,  Jianming Zhang ,  He Zhang ,  Yilin Wang ,  Zhe Lin ,  Ning Xu

IPC: G06T7/194 ,  G06T7/136 ,  G06T7/11 ,  G06T3/40 ,  G06T5/00

CPC classification number: G06T7/194 ,  G06T7/136 ,  G06T7/11 ,  G06T3/4053 ,  G06T3/4046 ,  G06T5/009 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that utilize a progressive refinement network to refine alpha mattes generated utilizing a mask-guided matting neural network. In particular, the disclosed systems can use the matting neural network to process a digital image and a coarse guidance mask to generate alpha mattes at discrete neural network layers. In turn, the disclosed systems can use the progressive refinement network to combine alpha mattes and refine areas of uncertainty. For example, the progressive refinement network can combine a core alpha matte corresponding to more certain core regions of a first alpha matte and a boundary alpha matte corresponding to uncertain boundary regions of a second, higher resolution alpha matte. Based on the combination of the core alpha matte and the boundary alpha matte, the disclosed systems can generate a final alpha matte for use in image matting processes.

公开(公告)号：US11681737B2

公开(公告)日：2023-06-20

申请号：US16843218

申请日：2020-04-08

Applicant: ADOBE INC.

Inventor： Handong Zhao ,  Ajinkya Kale ,  Xiaowei Jia ,  Zhe Lin

IPC: G06F16/43 ,  G06F16/45 ,  G06F16/438 ,  G06N3/04 ,  G06N3/08

CPC classification number: G06F16/43 ,  G06F16/438 ,  G06F16/45 ,  G06N3/04 ,  G06N3/08

Abstract: The present disclosure relates to a retrieval method including: generating a graph representing a set of users, items, and queries; generating clusters from the media items; generating embeddings for each cluster from embeddings of the items within the corresponding cluster; generating augmented query embeddings for each cluster from the embedding of the corresponding cluster and query embeddings of the queries; inputting the cluster embeddings and the augmented query embeddings to a layer of a graph convolutional network (GCN) to determine user embeddings of the users; inputting the embedding of the given user and a query embedding of the given query to a layer of the GCN to determine a user-specific query embedding; generating a score for each of the items based on the item embeddings and the user-specific query embedding; and presenting the items having the score exceeding a threshold.

公开(公告)号：US11663265B2

公开(公告)日：2023-05-30

申请号：US17104745

申请日：2020-11-25

Applicant: Adobe Inc.

Inventor： Zhe Lin ,  Shabnam Ghadar ,  Saeid Motiian ,  Ratheesh Kalarot ,  Baldo Faieta ,  Alireza Zaeemzadeh

IPC: G06F16/583 ,  G06F16/532 ,  G06N20/00 ,  G06F16/54 ,  G06F16/56 ,  G06F16/538

CPC classification number: G06F16/583 ,  G06F16/532 ,  G06F16/538 ,  G06F16/54 ,  G06F16/56 ,  G06N20/00

Abstract: A query image is received, along with a query to initiate a search process to find other images based on the query image. The query includes a preference value associated with an attribute, the preference value indicative of a level of emphasis to be placed on the attribute during the search. A full query vector, which is within a first dimensional space and representative of the query image, is generated. The full query vector is projected to a reduced dimensional space having a dimensionality lower than the first dimensional space, to generate a query vector. An attribute direction corresponding to the attribute is identified. A plurality of candidate vectors of the reduced dimensional space is searched, based on the attribute direction, the query vector, and the preference value, to identify a target vector of the plurality of candidate vectors. A target image, representative of the target vector, is displayed.

公开(公告)号：US20230153943A1

公开(公告)日：2023-05-18

申请号：US17455134

申请日：2021-11-16

Applicant: ADOBE INC.

Inventor： Jason Kuen ,  Jiuxiang Gu ,  Zhe Lin

IPC: G06T3/40 ,  G06K9/62 ,  G06N3/08 ,  G06N3/04

CPC classification number: G06T3/4046 ,  G06K9/6202 ,  G06N3/08 ,  G06N3/0454

Abstract: Systems and methods for image processing are described. The systems and methods include receiving a low-resolution image; generating a feature map based on the low-resolution image using an encoder of a student network, wherein the encoder of the student network is trained based on comparing a predicted feature map from the encoder of the student network and a fused feature map from a teacher network, and wherein the fused feature map represents a combination of first feature map from a high-resolution encoder of the teacher network and a second feature map from a low-resolution encoder of the teacher network; and decoding the feature map to obtain prediction information for the low-resolution image.

公开(公告)号：US20230126177A1

公开(公告)日：2023-04-27

申请号：US17452529

申请日：2021-10-27

Applicant: ADOBE INC.

Inventor： Ning Xu ,  Zhe Lin ,  Franck Dernoncourt

IPC: G06T5/00 ,  G06T11/60 ,  G10L15/22 ,  G06N3/08 ,  G06T5/50

Abstract: The present disclosure relates to systems and methods for automatically processing images based on a user request. In some examples, a request is divided into a retouching command (e.g., a global edit) and an inpainting command (e.g., a local edit). A retouching mask and an inpainting mask are generated to indicate areas where the edits will be applied. A photo-request attention and a multi-modal modulation process are applied to features representing the image, and a modified image that incorporates the user's request is generated using the modified features.

公开(公告)号：US20230123658A1

公开(公告)日：2023-04-20

申请号：US17502782

申请日：2021-10-15

Applicant: Adobe Inc.

Inventor： Yifan Liu ,  Jianming Zhang ,  He Zhang ,  Elya Shechtman ,  Zhe Lin

IPC: G06T15/60 ,  G06T11/00 ,  G06T7/70 ,  G06T7/194 ,  G06N3/04

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate a height map for a digital object portrayed in a digital image and further utilizes the height map to generate a shadow for the digital object. Indeed, in one or more embodiments, the disclosed systems generate (e.g., utilizing a neural network) a height map that indicates the pixels heights for pixels of a digital object portrayed in a digital image. The disclosed systems utilize the pixel heights, along with lighting information for the digital image, to determine how the pixels of the digital image project to create a shadow for the digital object. Further, in some implementations, the disclosed systems utilize the determined shadow projections to generate (e.g., utilizing another neural network) a soft shadow for the digital object. Accordingly, in some cases, the disclosed systems modify the digital image to include the shadow.

公开(公告)号：US11631234B2

公开(公告)日：2023-04-18

申请号：US16518810

申请日：2019-07-22

Applicant: Adobe Inc.

Inventor： Scott Cohen ,  Zhe Lin ,  Mingyang Ling

IPC: G06K9/00 ,  G06V10/20 ,  G06F16/535 ,  G06K9/62

Abstract: The present disclosure relates to an object selection system that accurately detects and optionally automatically selects user-requested objects (e.g., query objects) in digital images. For example, the object selection system builds and utilizes an object selection pipeline to determine which object detection neural network to utilize to detect a query object based on analyzing the object class of a query object. In particular, the object selection system can identify both known object classes as well as objects corresponding to unknown object classes.

公开(公告)号：US11605156B2

公开(公告)日：2023-03-14

申请号：US17812639

申请日：2022-07-14

Applicant: ADOBE INC.

Inventor： Zhe Lin ,  Yu Zeng ,  Jimei Yang ,  Jianming Zhang ,  Elya Shechtman

IPC: G06T5/00 ,  G06N3/04 ,  G06N3/08

Abstract: Methods and systems are provided for accurately filling holes, regions, and/or portions of images using iterative image inpainting. In particular, iterative inpainting utilize a confidence analysis of predicted pixels determined during the iterations of inpainting. For instance, a confidence analysis can provide information that can be used as feedback to progressively fill undefined pixels that comprise the holes, regions, and/or portions of an image where information for those respective pixels is not known. To allow for accurate image inpainting, one or more neural networks can be used. For instance, a coarse result neural network (e.g., a GAN comprised of a generator and a discriminator) and a fine result neural network (e.g., a GAN comprised of a generator and two discriminators). The image inpainting system can use such networks to predict an inpainting image result that fills the hole, region, and/or portion of the image using predicted pixels and generates a corresponding confidence map of the predicted pixels.