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公开(公告)号：US20230222762A1
公开(公告)日：2023-07-13
申请号：US17573041
申请日：2022-01-11
Applicant: Adobe Inc.
Inventor： Maksym Andriushchenko , John Collomosse , Xiaoyang Li , Geoffrey Oxholm
IPC: G06V10/75 , G06F16/583 , G06F16/58 , G06V10/72 , G06V10/771 , G06N3/08
CPC classification number: G06V10/751 , G06F16/583 , G06F16/5866 , G06V10/72 , G06V10/771 , G06N3/084
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media that utilize a deep visual fingerprinting model with parameters learned from robust contrastive learning to identify matching digital images and image provenance information. For example, the disclosed systems utilize an efficient learning procedure that leverages training on bounded adversarial examples to more accurately identify digital images (including adversarial images) with a small computational overhead. To illustrate, the disclosed systems utilize a first objective function that iteratively identifies augmentations to increase contrastive loss. Moreover, the disclosed systems utilize a second objective function that iteratively learns parameters of a deep visual fingerprinting model to reduce the contrastive loss. With these learned parameters, the disclosed systems utilize the deep visual fingerprinting model to generate visual fingerprints for digital images, retrieve and match digital images, and provide digital image provenance information.
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公开(公告)号：US20210311936A1
公开(公告)日：2021-10-07
申请号：US17350127
申请日：2021-06-17
Applicant: Adobe Inc.
Inventor： Hailin Jin , John Collomosse
IPC: G06F16/248 , G06N3/08 , G06F16/51 , G06F16/28 , G06F16/532
Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for guided visual search. A visual search query can be represented as a sketch sequence that includes ordering information of the constituent strokes in the sketch. The visual search query can be encoded into a structural search encoding in a common search space by a structural neural network. Indexed visual search results can be identified in the common search space and clustered in an auxiliary semantic space. Sketch suggestions can be identified from a plurality of indexed sketches in the common search space. A sketch suggestion can be identified for each semantic cluster of visual search results and presented with the cluster to guide a user towards relevant content through an iterative search process. Selecting a sketch suggestion as a target sketch can automatically transform the visual search query to the target sketch via adversarial images.
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Patent Agency Ranking
公开(公告)号：US20210264282A1
公开(公告)日：2021-08-26
申请号：US16796878
申请日：2020-02-20
Applicant: Adobe Inc.
Inventor： John Collomosse , Hailin Jim
Abstract: Techniques and systems are provided for configuring neural networks to perform certain image manipulation operations. For instance, in response to obtaining an image for manipulation, an image manipulation system determines the fitness scores for a set of neural networks resulting from the processing of a noise map. Based on these fitness scores, the image manipulation system selects a subset of the set of neural networks for cross-breeding into a new generation of neural networks. The image manipulation system evaluates the performance of this new generation of neural networks and continues cross-breeding this neural networks until a fitness threshold is satisfied. From the final generation of neural networks, the image manipulation system selects a neural network that provides a desired output and uses the neural network to generate the manipulated image.
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公开(公告)号：US11068493B2
公开(公告)日：2021-07-20
申请号：US16183228
申请日：2018-11-07
Applicant: ADOBE INC.
Inventor： Hailin Jin , John Collomosse
IPC: G06F16/248 , G06N3/08 , G06F16/51 , G06F16/28 , G06F16/532
Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for guided visual search. A visual search query can be represented as a sketch sequence that includes ordering information of the constituent strokes in the sketch. The visual search query can be encoded into a structural search encoding in a common search space by a structural neural network. Indexed visual search results can be identified in the common search space and clustered in an auxiliary semantic space. Sketch suggestions can be identified from a plurality of indexed sketches in the common search space. A sketch suggestion can be identified for each semantic cluster of visual search results and presented with the cluster to guide a user towards relevant content through an iterative search process. Selecting a sketch suggestion as a target sketch can automatically transform the visual search query to the target sketch via adversarial images.
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公开(公告)号：US20240430515A1
公开(公告)日：2024-12-26
申请号：US18822424
申请日：2024-09-02
Applicant: Adobe, Inc. , University of Surrey
Inventor： Alexander Black , Van Tu Bui , John Collomosse , Simon Jenni , Viswanathan Swaminathan
IPC: H04N21/434 , G06F16/732 , G06F16/78 , H04N21/84 , H04N21/845
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media that utilize deep learning to map query videos to known videos so as to identify a provenance of the query video or identify editorial manipulations of the query video relative to a known video. For example, the video comparison system includes a deep video comparator model that generates and compares visual and audio descriptors utilizing codewords and an inverse index. The deep video comparator model is robust and ignores discrepancies due to benign transformations that commonly occur during electronic video distribution.
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公开(公告)号：US11966849B2
公开(公告)日：2024-04-23
申请号：US16796878
申请日：2020-02-20
Applicant: Adobe Inc.
Inventor： John Collomosse , Hailin Jin
Abstract: Techniques and systems are provided for configuring neural networks to perform certain image manipulation operations. For instance, in response to obtaining an image for manipulation, an image manipulation system determines the fitness scores for a set of neural networks resulting from the processing of a noise map. Based on these fitness scores, the image manipulation system selects a subset of the set of neural networks for cross-breeding into a new generation of neural networks. The image manipulation system evaluates the performance of this new generation of neural networks and continues cross-breeding this neural networks until a fitness threshold is satisfied. From the final generation of neural networks, the image manipulation system selects a neural network that provides a desired output and uses the neural network to generate the manipulated image.
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公开(公告)号：US20210312698A1
公开(公告)日：2021-10-07
申请号：US16838429
申请日：2020-04-02
Applicant: Adobe Inc.
Inventor： Tong He , John Collomosse , Hailin Jin
Abstract: Systems, methods, and non-transitory computer-readable media are disclosed for utilizing an encoder-decoder architecture to learn a volumetric 3D representation of an object using digital images of the object from multiple viewpoints to render novel views of the object. For instance, the disclosed systems can utilize patch-based image feature extraction to extract lifted feature representations from images corresponding to different viewpoints of an object. Furthermore, the disclosed systems can model view-dependent transformed feature representations using learned transformation kernels. In addition, the disclosed systems can recurrently and concurrently aggregate the transformed feature representations to generate a 3D voxel representation of the object. Furthermore, the disclosed systems can sample frustum features using the 3D voxel representation and transformation kernels. Then, the disclosed systems can utilize a patch-based neural rendering approach to render images from frustum feature patches to display a view of the object from various viewpoints.
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