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公开(公告)号：US10789694B1
公开(公告)日：2020-09-29
申请号：US16032938
申请日：2018-07-11
Applicant: Apple Inc.
Inventor： Bartlomiej W. Rymkowski , Francesco Rossi
Abstract: Artistic styles extracted from one or more source images may be applied to one or more target images, e.g., in the form of stylized images and/or stylized video sequences. The extracted artistic style may be stored as a plurality of layers in a neural network, which neural network may be further optimized, e.g., via the fusion of various elements of the network's architectures. An optimized network architecture may be determined for each processing environment in which the network will be applied. The artistic style may be applied to the obtained images and/or video sequence of images using various optimization methods, such as the use of scalars to control the resolution of the unstylized and stylized images, temporal consistency constraints, as well as the use of dynamically adjustable or selectable versions of Deep Neural Networks (DNN) that are responsive to system performance parameters, such as available processing resources and thermal capacity.
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公开(公告)号：US11367163B2
公开(公告)日：2022-06-21
申请号：US16794824
申请日：2020-02-19
Applicant: Apple Inc.
Inventor： Francesco Rossi , Marco Zuliani , Bartlomiej W. Rymkowski , Albert Antony , Brian P. Keene , Xiaojin Shi
Abstract: Artistic styles extracted from source images may be applied to target images to generate stylized images and/or video sequences. The extracted artistic styles may be stored as a plurality of layers in one or more neural networks, which neural networks may be further optimized, e.g., via the fusion of various elements of the networks' architectures. The artistic style may be applied to the target images and/or video sequences using various optimization methods, such as the use of a first version of the neural network by a first processing device at a first resolution to generate one or more sets of parameters (e.g., scaling and/or biasing parameters), which parameters may then be mapped for use by a second version of the neural network by a second processing device at a second resolution. Analogous multi-processing device and/or multi-network solutions may also be applied to other complex image processing tasks for increased efficiency.
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公开(公告)号：US20200380639A1
公开(公告)日：2020-12-03
申请号：US16794824
申请日：2020-02-19
Applicant: Apple Inc.
Inventor： Francesco Rossi , Marco Zuliani , Bartlomiej W. Rymkowski , Albert Antony , Brian P. Keene , Xiaojin Shi
Abstract: Artistic styles extracted from source images may be applied to target images to generate stylized images and/or video sequences. The extracted artistic styles may be stored as a plurality of layers in one or more neural networks, which neural networks may be further optimized, e.g., via the fusion of various elements of the networks' architectures. The artistic style may be applied to the target images and/or video sequences using various optimization methods, such as the use of a first version of the neural network by a first processing device at a first resolution to generate one or more sets of parameters (e.g., scaling and/or biasing parameters), which parameters may then be mapped for use by a second version of the neural network by a second processing device at a second resolution. Analogous multi-processing device and/or multi-network solutions may also be applied to other complex image processing tasks for increased efficiency.
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公开(公告)号：US10664963B1
公开(公告)日：2020-05-26
申请号：US16032879
申请日：2018-07-11
Applicant: Apple Inc.
Inventor： Francesco Rossi , Xiaohuan C. Wang , Bartlomiej W. Rymkowski , Xiaojin Shi , Marco Zuliani , Alexey Marinichev
Abstract: Artistic styles extracted from one or more source images may be applied to one or more target images, e.g., in the form of stylized images and/or stylized video sequences. The extracted artistic style may be stored as a plurality of layers in a neural network, which neural network may be further optimized, e.g., via the fusion of various elements of the network's architectures. An optimized network architecture may be determined for each processing environment in which the network will be applied. The artistic style may be applied to the obtained images and/or video sequence of images using various optimization methods, such as the use of scalars to control the resolution of the unstylized and stylized images, temporal consistency constraints, as well as the use of dynamically adjustable or selectable versions of Deep Neural Networks (DNN) that are responsive to system performance parameters, such as available processing resources and thermal capacity.
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公开(公告)号：US10147459B2
公开(公告)日：2018-12-04
申请号：US15273695
申请日：2016-09-22
Applicant: Apple Inc.
Inventor： Bartlomiej W. Rymkowski , Marco Zuliani
IPC: G11B27/00 , H04N5/93 , G11B27/031 , G06T11/60 , G06K9/00
Abstract: Techniques are disclosed herein for applying an artistic style extracted from one or more source images, e.g., paintings, to one or more target images. The extracted artistic style may then be stored as a plurality of layers in a neural network. In some embodiments, two or more stylized target images may be combined and stored as a stylized video sequence. The artistic style may be applied to the target images in the stylized video sequence using various optimization methods and/or pixel- and feature-based regularization techniques in a way that prevents excessive content pixel fluctuations between images and preserves smoothness in the assembled stylized video sequence. In other embodiments, a user may be able to semantically annotate locations of undesired artifacts in a target image, as well as portion(s) of a source image from which a style may be extracted and used to replace the undesired artifacts in the target image.
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Patent Agency Ranking
公开(公告)号：US20180082715A1
公开(公告)日：2018-03-22
申请号：US15273695
申请日：2016-09-22
Applicant: Apple Inc.
Inventor： Bartlomiej W. Rymkowski , Marco Zuliani
IPC: G11B27/031 , G06T11/60 , G06K9/00
CPC classification number: G11B27/031 , G06K9/00664 , G06K9/00718 , G06T11/60
Abstract: Techniques are disclosed herein for applying an artistic style extracted from one or more source images, e.g., paintings, to one or more target images. The extracted artistic style may then be stored as a plurality of layers in a neural network. In some embodiments, two or more stylized target images may be combined and stored as a stylized video sequence. The artistic style may be applied to the target images in the stylized video sequence using various optimization methods and/or pixel- and feature-based regularization techniques in a way that prevents excessive content pixel fluctuations between images and preserves smoothness in the assembled stylized video sequence. In other embodiments, a user may be able to semantically annotate locations of undesired artifacts in a target image, as well as portion(s) of a source image from which a style may be extracted and used to replace the undesired artifacts in the target image.
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公开(公告)号：US10909657B1
公开(公告)日：2021-02-02
申请号：US16032844
申请日：2018-07-11
Applicant: Apple Inc.
Inventor： Francesco Rossi , Xiaohuan C. Wang , Brian E. Walsh , Bartlomiej W. Rymkowski , Xiaojin Shi , Marco Zuliani , Alexey Marinichev , Benjamin Poulain , Omid Khalili
Abstract: Artistic styles extracted from one or more source images may be applied to one or more target images, e.g., in the form of stylized images and/or stylized video sequences. The extracted artistic style may be stored as a plurality of layers in a neural network, which neural network may be further optimized, e.g., via the fusion of various elements of the network's architectures. An optimized network architecture may be determined for each processing environment in which the network will be applied. The artistic style may be applied to the obtained images and/or video sequence of images using various optimization methods, such as the use of scalars to control the resolution of the unstylized and stylized images, temporal consistency constraints, as well as the use of dynamically adjustable or selectable versions of Deep Neural Networks (DNN) that are responsive to system performance parameters, such as available processing resources and thermal capacity.
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公开(公告)号：US10664718B1
公开(公告)日：2020-05-26
申请号：US16032909
申请日：2018-07-11
Applicant: Apple Inc.
Inventor： Bartlomiej W. Rymkowski , Francesco Rossi
Abstract: Artistic styles extracted from one or more source images may be applied to one or more target images, e.g., in the form of stylized images and/or stylized video sequences. The extracted artistic style may be stored as a plurality of layers in a neural network, which neural network may be further optimized, e.g., via the fusion of various elements of the network's architectures. An optimized network architecture may be determined for each processing environment in which the network will be applied. The artistic style may be applied to the obtained images and/or video sequence of images using various optimization methods, such as the use of scalars to control the resolution of the unstylized and stylized images, temporal consistency constraints, as well as the use of dynamically adjustable or selectable versions of Deep Neural Networks (DNN) that are responsive to system performance parameters, such as available processing resources and thermal capacity.
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公开(公告)号：US10198839B2
公开(公告)日：2019-02-05
申请号：US15273674
申请日：2016-09-22
Applicant: Apple Inc.
Inventor： Bartlomiej W. Rymkowski , Marco Zuliani
Abstract: Techniques are disclosed herein for applying an artistic style extracted from one or more source images, e.g., paintings, to one or more target images. The extracted artistic style may then be stored as a plurality of layers in a neural network. In some embodiments, two or more stylized target images may be combined and stored as a stylized video sequence. The artistic style may be applied to the target images in the stylized video sequence using various optimization methods and/or pixel- and feature-based regularization techniques in a way that prevents excessive content pixel fluctuations between images and preserves smoothness in the assembled stylized video sequence. In other embodiments, a user may be able to semantically annotate locations of undesired artifacts in a target image, as well as portion(s) of a source image from which a style may be extracted and used to replace the undesired artifacts in the target image.
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公开(公告)号：US20180082407A1
公开(公告)日：2018-03-22
申请号：US15273674
申请日：2016-09-22
Applicant: Apple Inc.
Inventor： Bartlomiej W. Rymkowski , Marco Zuliani
CPC classification number: G06T11/60
Abstract: Techniques are disclosed herein for applying an artistic style extracted from one or more source images, e.g., paintings, to one or more target images. The extracted artistic style may then be stored as a plurality of layers in a neural network. In some embodiments, two or more stylized target images may be combined and stored as a stylized video sequence. The artistic style may be applied to the target images in the stylized video sequence using various optimization methods and/or pixel- and feature-based regularization techniques in a way that prevents excessive content pixel fluctuations between images and preserves smoothness in the assembled stylized video sequence. In other embodiments, a user may be able to semantically annotate locations of undesired artifacts in a target image, as well as portion(s) of a source image from which a style may be extracted and used to replace the undesired artifacts in the target image.
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