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公开(公告)号：US11677897B2
公开(公告)日：2023-06-13
申请号：US17073697
申请日：2020-10-19
Applicant: Adobe Inc.
Inventor： Wentian Zhao , Kun Wan , Xin Lu , Jen-Chan Jeff Chien
CPC classification number: H04N5/2621 , G06T5/003 , G06V10/40 , G06V10/56 , G06V10/82 , H04N5/265 , H04N23/631 , H04N23/632
Abstract: Methods, systems, and non-transitory computer readable media are disclosed for generating artistic images by applying an artistic-effect to one or more frames of a video stream or digital images. In one or more embodiments, the disclosed system captures a video stream utilizing a camera of a computing device. The disclosed system deploys a distilled artistic-effect neural network on the computing device to generate an artistic version of the captured video stream at a first resolution in real time. The disclosed system can provide the artistic video stream for display via the computing device. Based on an indication of a capture event, the disclosed system utilizes the distilled artistic-effect neural network to generate an artistic image at a higher resolution than the artistic video stream. Furthermore, the disclosed system tunes and utilizes an artistic-effect patch generative adversarial neural network to modify parameters for the distilled artistic-effect neural network.
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公开(公告)号：US11625813B2
公开(公告)日：2023-04-11
申请号：US17085491
申请日：2020-10-30
Applicant: Adobe Inc.
Inventor： Sheng-Wei Huang , Wentian Zhao , Kun Wan , Zichuan Liu , Xin Lu , Jen-Chan Jeff Chien
Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for accurately and efficiently removing objects from digital images taken from a camera viewfinder stream. For example, the disclosed systems access digital images from a camera viewfinder stream in connection with an undesired moving object depicted in the digital images. The disclosed systems generate a temporal window of the digital images concatenated with binary masks indicating the undesired moving object in each digital image. The disclosed systems further utilizes a 3D to 2D generator as part of a 3D to 2D generative adversarial neural network in connection with the temporal window to generate a target digital image with the region associated with the undesired moving object in-painted. In at least one embodiment, the disclosed systems provide the target digital image to a camera viewfinder display to show a user how a future digital photograph will look without the undesired moving object.
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3.发明申请公开(公告)号：US20220122357A1
公开(公告)日：2022-04-21
申请号：US17563901
申请日：2021-12-28
Applicant: Adobe Inc.
Inventor： Wentian Zhao , Seokhwan Kim , Ning Xu , Hailin Jin
Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media for generating a response to a question received from a user during display or playback of a video segment by utilizing a query-response-neural network. The disclosed systems can extract a query vector from a question corresponding to the video segment using the query-response-neural network. The disclosed systems further generate context vectors representing both visual cues and transcript cues corresponding to the video segment using context encoders or other layers from the query-response-neural network. By utilizing additional layers from the query-response-neural network, the disclosed systems generate (i) a query-context vector based on the query vector and the context vectors, and (ii) candidate-response vectors representing candidate responses to the question from a domain-knowledge base or other source. To respond to a user's question, the disclosed systems further select a response from the candidate responses based on a comparison of the query-context vector and the candidate-response vectors.
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公开(公告)号：US20240346234A1
公开(公告)日：2024-10-17
申请号：US18300721
申请日：2023-04-14
Applicant: ADOBE INC.
Inventor： Xinyang Zhang , Wentian Zhao , Xin Lu , Jen-Chan Chien
IPC: G06F40/166 , G06F40/103 , G06V30/41
CPC classification number: G06F40/166 , G06F40/103 , G06V30/41
Abstract: Systems and methods for document processing are provided. One aspect of the systems and methods includes obtaining a prompt including a document description describing a plurality of elements. A plurality of image assets are generated based on the prompt using a generative neural network. In some cases, the plurality of image assets correspond to the plurality of elements of the document description. A structured document is then generated that matches the document description. In some cases the structured document includes the plurality of image assets and metadata describing a relationship between the plurality of image assets.
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公开(公告)号：US11335004B2
公开(公告)日：2022-05-17
申请号：US16988408
申请日：2020-08-07
Applicant: Adobe Inc.
Inventor： Zichuan Liu , Wentian Zhao , Shitong Wang , He Qin , Yumin Jia , Yeojin Kim , Xin Lu , Jen-Chan Chien
IPC: G06T7/11
Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate refined segmentation masks for digital visual media items. For example, in one or more embodiments, the disclosed systems utilize a segmentation refinement neural network to generate an initial segmentation mask for a digital visual media item. The disclosed systems further utilize the segmentation refinement neural network to generate one or more refined segmentation masks based on uncertainly classified pixels identified from the initial segmentation mask. To illustrate, in some implementations, the disclosed systems utilize the segmentation refinement neural network to redetermine whether a set of uncertain pixels corresponds to one or more objects depicted in the digital visual media item based on low-level (e.g., local) feature values extracted from feature maps generated for the digital visual media item.
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Patent Agency Ranking
公开(公告)号：US20220124257A1
公开(公告)日：2022-04-21
申请号：US17073697
申请日：2020-10-19
Applicant: Adobe Inc.
Inventor： Wentian Zhao , Kun Wan , Xin Lu , Jen-Chan Jeff Chien
Abstract: Methods, systems, and non-transitory computer readable media are disclosed for generating artistic images by applying an artistic-effect to one or more frames of a video stream or digital images. In one or more embodiments, the disclosed system captures a video stream utilizing a camera of a computing device. The disclosed system deploys a distilled artistic-effect neural network on the computing device to generate an artistic version of the captured video stream at a first resolution in real time. The disclosed system can provide the artistic video stream for display via the computing device. Based on an indication of a capture event, the disclosed system utilizes the distilled artistic-effect neural network to generate an artistic image at a higher resolution than the artistic video stream. Furthermore, the disclosed system tunes and utilizes an artistic-effect patch generative adversarial neural network to modify parameters for the distilled artistic-effect neural network.
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公开(公告)号：US12026857B2
公开(公告)日：2024-07-02
申请号：US18298146
申请日：2023-04-10
Applicant: Adobe Inc.
Inventor： Sheng-Wei Huang , Wentian Zhao , Kun Wan , Zichuan Liu , Xin Lu , Jen-Chan Jeff Chien
IPC: G06T5/77 , G06F18/2134 , G06T7/73 , H04N23/63
CPC classification number: G06T5/77 , G06F18/2134 , G06T7/73 , H04N23/631 , G06T2207/10016 , G06T2207/20081
Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for accurately and efficiently removing objects from digital images taken from a camera viewfinder stream. For example, the disclosed systems access digital images from a camera viewfinder stream in connection with an undesired moving object depicted in the digital images. The disclosed systems generate a temporal window of the digital images concatenated with binary masks indicating the undesired moving object in each digital image. The disclosed systems further utilizes a generator as part of a 3D to 2D generative adversarial neural network in connection with the temporal window to generate a target digital image with the region associated with the undesired moving object in-painted. In at least one embodiment, the disclosed systems provide the target digital image to a camera viewfinder display to show a user how a future digital photograph will look without the undesired moving object.
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公开(公告)号：US20230262189A1
公开(公告)日：2023-08-17
申请号：US18309410
申请日：2023-04-28
Applicant: Adobe Inc.
Inventor： Wentian Zhao , Kun Wan , Xin Lu , Jen-Chan Jeff Chien
CPC classification number: H04N5/2621 , H04N5/265 , G06T5/003 , G06V10/82 , G06V10/40 , G06V10/56 , H04N23/631 , H04N23/632
Abstract: Methods, systems, and non-transitory computer readable media are disclosed for generating artistic images by applying an artistic-effect to one or more frames of a video stream or digital images. In one or more embodiments, the disclosed system captures a video stream utilizing a camera of a computing device. The disclosed system deploys a distilled artistic-effect neural network on the computing device to generate an artistic version of the captured video stream at a first resolution in real time. The disclosed system can provide the artistic video stream for display via the computing device. Based on an indication of a capture event, the disclosed system utilizes the distilled artistic-effect neural network to generate an artistic image at a higher resolution than the artistic video stream. Furthermore, the disclosed system tunes and utilizes an artistic-effect patch generative adversarial neural network to modify parameters for the distilled artistic-effect neural network.
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公开(公告)号：US20220245824A1
公开(公告)日：2022-08-04
申请号：US17660361
申请日：2022-04-22
Applicant: Adobe Inc.
Inventor： Zichuan Liu , Wentian Zhao , Shitong Wang , He Qin , Yumin Jia , Yeojin Kim , Xin Lu , Jen-Chan Chien
IPC: G06T7/11
Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate refined segmentation masks for digital visual media items. For example, in one or more embodiments, the disclosed systems utilize a segmentation refinement neural network to generate an initial segmentation mask for a digital visual media item. The disclosed systems further utilize the segmentation refinement neural network to generate one or more refined segmentation masks based on uncertainly classified pixels identified from the initial segmentation mask. To illustrate, in some implementations, the disclosed systems utilize the segmentation refinement neural network to redetermine whether a set of uncertain pixels corresponds to one or more objects depicted in the digital visual media item based on low-level (e.g., local) feature values extracted from feature maps generated for the digital visual media item.
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公开(公告)号：US20230274400A1
公开(公告)日：2023-08-31
申请号：US18298146
申请日：2023-04-10
Applicant: Adobe Inc.
Inventor： Sheng-Wei Huang , Wentian Zhao , Kun Wan , Zichuan Liu , Xin Lu , Jen-Chan Jeff Chien
IPC: G06T5/00 , G06T7/73 , G06F18/2134 , H04N23/63
CPC classification number: G06T5/005 , G06F18/2134 , G06T7/73 , H04N23/631 , G06T2207/10016 , G06T2207/20081
Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for accurately and efficiently removing objects from digital images taken from a camera viewfinder stream. For example, the disclosed systems access digital images from a camera viewfinder stream in connection with an undesired moving object depicted in the digital images. The disclosed systems generate a temporal window of the digital images concatenated with binary masks indicating the undesired moving object in each digital image. The disclosed systems further utilizes a generator as part of a 3D to 2D generative adversarial neural network in connection with the temporal window to generate a target digital image with the region associated with the undesired moving object in-painted. In at least one embodiment, the disclosed systems provide the target digital image to a camera viewfinder display to show a user how a future digital photograph will look without the undesired moving object.
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