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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：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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Patent Agency Ranking
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：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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公开(公告)号：US20220164666A1
公开(公告)日：2022-05-26
申请号：US17100651
申请日：2020-11-20
Applicant: Adobe Inc.
Inventor： Zichuan Liu , Kun Wan , Xin Lu
Abstract: A method for performing efficient mixed-precision search for an artificial neural network (ANN) includes training the ANN by sampling selected candidate quantizers of a bank of candidate quantizer and updating network parameters for a next iteration based on outputs of layers of the ANN. The outputs are computed by processing quantized data with operators (e.g., convolution). The quantizers converge to optimal bit-widths that reduce classification losses bounded by complexity constrains.
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公开(公告)号：US20220138913A1
公开(公告)日：2022-05-05
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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