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公开(公告)号：US20190286716A1
公开(公告)日：2019-09-19
申请号：US15924791
申请日：2018-03-19
Applicant: Adobe Inc.
Inventor： Zhe Lin , Yingwei Li
Abstract: Online dictionary extension of word vectors techniques and systems are described that are configured to provide online extension of existing word vector dictionaries and thus overcome the failures of conventional techniques. In one example, a dictionary extension system is employed by a computing system to extend a word vector dictionary to incorporate a new word in an online manner Co-occurrence information is estimated for the new word with respect to the words in the existing dictionary. This is done by estimating co-occurrence information with respect to a large word set based on the existing dictionary and sparse co-occurrence information for the new word. The estimated co-occurrence information is utilized to estimate a new word vector associated with the new word by projecting the estimated co-occurrence information onto the existing word vector dictionary. An extended dictionary is created incorporating the original dictionary and the estimated new word vector.
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公开(公告)号：US20190279074A1
公开(公告)日：2019-09-12
申请号：US15913829
申请日：2018-03-06
Applicant: Adobe Inc.
Inventor： Zhe Lin , Yufei Wang , Xiaohui Shen , Scott David Cohen , Jianming Zhang
Abstract: Semantic segmentation techniques and systems are described that overcome the challenges of limited availability of training data to describe the potentially millions of tags that may be used to describe semantic classes in digital images. In one example, the techniques are configured to train neural networks to leverage different types of training datasets using sequential neural networks and use of vector representations to represent the different semantic classes.
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公开(公告)号：US10410351B2
公开(公告)日：2019-09-10
申请号：US16116609
申请日：2018-08-29
Applicant: Adobe Inc.
Inventor： Zhe Lin , Xin Lu , Xiaohui Shen , Jimei Yang , Chenxi Liu
Abstract: The invention is directed towards segmenting images based on natural language phrases. An image and an n-gram, including a sequence of tokens, are received. An encoding of image features and a sequence of token vectors are generated. A fully convolutional neural network identifies and encodes the image features. A word embedding model generates the token vectors. A recurrent neural network (RNN) iteratively updates a segmentation map based on combinations of the image feature encoding and the token vectors. The segmentation map identifies which pixels are included in an image region referenced by the n-gram. A segmented image is generated based on the segmentation map. The RNN may be a convolutional multimodal RNN. A separate RNN, such as a long short-term memory network, may iteratively update an encoding of semantic features based on the order of tokens. The first RNN may update the segmentation map based on the semantic feature encoding.
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公开(公告)号：US20190252002A1
公开(公告)日：2019-08-15
申请号：US16395041
申请日：2019-04-25
Applicant: Adobe Inc.
Inventor： Zhihong Ding , Zhe Lin , Xiaohui Shen , Michael Kaplan , Jonathan Brandt
CPC classification number: G11B27/11 , G06K9/00744 , G06K9/3241 , G06T7/97 , G06T11/60 , G06T2207/10016 , G11B27/031 , G11B27/28 , G11B27/326
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.
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公开(公告)号：US20190244327A1
公开(公告)日：2019-08-08
申请号：US16384593
申请日：2019-04-15
Applicant: Adobe Inc.
Inventor： Zhe Lin , Radomir Mech , Xiaohui Shen , Brian L. Price , Jianming Zhang , Anant Gilra , Jen-Chan Jeff Chien
CPC classification number: G06T3/40 , G06K9/4671 , G06T3/0012 , G06T11/60 , G06T2210/22
Abstract: Image cropping suggestion using multiple saliency maps is described. In one or more implementations, component scores, indicative of visual characteristics established for visually-pleasing croppings, are computed for candidate image croppings using multiple different saliency maps. The visual characteristics on which a candidate image cropping is scored may be indicative of its composition quality, an extent to which it preserves content appearing in the scene, and a simplicity of its boundary. Based on the component scores, the croppings may be ranked with regard to each of the visual characteristics. The rankings may be used to cluster the candidate croppings into groups of similar croppings, such that croppings in a group are different by less than a threshold amount and croppings in different groups are different by at least the threshold amount. Based on the clustering, croppings may then be chosen, e.g., to present them to a user for selection.
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Patent Agency Ranking
296.发明授权公开(公告)号：US10346727B2
公开(公告)日：2019-07-09
申请号：US15429769
申请日：2017-02-10
Applicant: Adobe Inc.
Inventor： Zhe Lin , Mai Long , Jonathan Brandt , Hailin Jin , Chen Fang
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.
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297.发明申请公开(公告)号：US20250139748A1
公开(公告)日：2025-05-01
申请号：US19011235
申请日：2025-01-06
Applicant: Adobe Inc.
Inventor： Sohrab Amirghodsi , Lingzhi Zhang , Zhe Lin , Connelly Barnes , Elya Shechtman
IPC: G06T5/77 , G06N3/08 , G06T3/4053 , G06T7/11 , G06T7/50
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately, efficiently, and flexibly generating modified digital images utilizing a guided inpainting approach that implements a patch match model informed by a deep visual guide. In particular, the disclosed systems can utilize a visual guide algorithm to automatically generate guidance maps to help identify replacement pixels for inpainting regions of digital images utilizing a patch match model. For example, the disclosed systems can generate guidance maps in the form of structure maps, depth maps, or segmentation maps that respectively indicate the structure, depth, or segmentation of different portions of digital images. Additionally, the disclosed systems can implement a patch match model to identify replacement pixels for filling regions of digital images according to the structure, depth, and/or segmentation of the digital images.
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298.发明申请公开(公告)号：US20250124544A1
公开(公告)日：2025-04-17
申请号：US18487764
申请日：2023-10-16
Applicant: ADOBE INC.
Inventor： Taesung Park , Qing Liu , Zhe Lin , Sohrab Amirghodsi , Elya Shechtman
Abstract: Systems and methods for upsampling low-resolution content within a high-resolution image include obtaining a composite image and a mask. The composite image includes a high-resolution region and a low-resolution region. An upsampling network identifies the low-resolution region of the composite image based on the mask and generates an upsampled composite image based on the composite image and the mask. The upsampled composite image comprises higher frequency details in the low-resolution region than the composite image.
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公开(公告)号：US12271983B2
公开(公告)日：2025-04-08
申请号：US17809494
申请日：2022-06-28
Applicant: Adobe Inc.
Inventor： Zhifei Zhang , Zhe Lin , Scott Cohen , Kevin Gary Smith
IPC: G06T11/60 , G06F3/0482 , G06F16/532 , G06T11/20
Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that implements related image search and image modification processes using various search engines and a consolidated graphical user interface. For instance, in one or more embodiments, the disclosed systems receive an input digital image and search input and further modify the input digital image using the image search results retrieved in response to the search input. In some cases, the search input includes a multi-modal search input having multiple queries (e.g., an image query and a text query), and the disclosed systems retrieve the image search results utilizing a weighted combination of the queries. In some implementations, the disclosed systems generate an input embedding for the search input (e.g., the multi-modal search input) and retrieve the image search results using the input embedding.
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公开(公告)号：US20250095393A1
公开(公告)日：2025-03-20
申请号：US18470778
申请日：2023-09-20
Applicant: ADOBE INC.
Inventor： Ziyan Yang , Kushal Kafle , Zhe Lin , Scott Cohen , Zhihong Ding
IPC: G06V20/70 , G06F40/205 , G06V10/25 , G06V10/774
Abstract: A method, apparatus, and non-transitory computer readable medium for image processing are described. Embodiments of the present disclosure obtain an image and an input text including a subject from the image and a location of the subject in the image. An image encoder encodes the image to obtain an image embedding. A text encoder encodes the input text to obtain a text embedding. An image processing apparatus based on the present disclosure generates an output text based on the image embedding and the text embedding. In some examples, the output text includes a relation of the subject to an object from the image and a location of the object in the image.
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