-
公开(公告)号：US11055887B2
公开(公告)日：2021-07-06
申请号：US16205010
申请日：2018-11-29
Applicant: Adobe Inc.
Inventor： Yumin Jia , Xin Lu , Jen-Chan Chien
Abstract: Facial skin mask generated by a digital content creation system is described. The digital content creation system includes digital effects on skin in facial regions of digital content with efficiency and accuracy. Upon identifying a facial region within digital content, the system generates a first regional skin mask, a second regional skin mask, and combines both of the first and second regional skin masks to generate a facial skin mask indicative of skin of the identified facial regions depicted in digital content. The digital content creation system then modifies digital content by applying user selected digital effects to the skin of the facial region using the generated facial skin mask.
-
公开(公告)号：US11869172B2
公开(公告)日：2024-01-09
申请号：US18055161
申请日：2022-11-14
Applicant: Adobe Inc.
Inventor： Haiting Lin , Yumin Jia , Jen-Chan Chien
Abstract: Embodiments are disclosed for generating lens blur effects. The disclosed systems and methods comprise receiving a request to apply a lens blur effect to an image, the request identifying an input image and a first disparity map, generating a plurality of disparity maps and a plurality of distance maps based on the first disparity map, splatting influences of pixels of the input image using a plurality of reshaped kernel gradients, gathering aggregations of the splatted influences, and determining a lens blur for a first pixel of the input image in an output image based on the gathered aggregations of the splatted influences.
-
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.
-
公开(公告)号：US20220121841A1
公开(公告)日：2022-04-21
申请号：US17075207
申请日：2020-10-20
Applicant: Adobe Inc.
Inventor： Jinoh Oh , Xin Lu , Gahye Park , Jen-Chan Jeff Chien , Yumin Jia
Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for utilizing a machine learning model trained to determine subtle pose differentiations to analyze a repository of captured digital images of a particular user to automatically capture digital images portraying the user. For example, the disclosed systems can utilize a convolutional neural network to determine a pose/facial expression similarity metric between a sample digital image from a camera viewfinder stream of a client device and one or more previously captured digital images portraying the user. The disclosed systems can determine that the similarity metric satisfies a similarity threshold, and automatically capture a digital image utilizing a camera device of the client device. Thus, the disclosed systems can automatically and efficiently capture digital images, such as selfies, that accurately match previous digital images portraying a variety of unique facial expressions specific to individual users.
-
公开(公告)号：US20200175736A1
公开(公告)日：2020-06-04
申请号：US16205010
申请日：2018-11-29
Applicant: Adobe Inc.
Inventor： Yumin Jia , Xin Lu , Jen-Chan Chien
Abstract: Facial skin mask generated by a digital content creation system is described. The digital content creation system includes digital effects on skin in facial regions of digital content with efficiency and accuracy. Upon identifying a facial region within digital content, the system generates a first regional skin mask, a second regional skin mask, and combines both of the first and second regional skin masks to generate a facial skin mask indicative of skin of the identified facial regions depicted in digital content. The digital content creation system then modifies digital content by applying user selected digital effects to the skin of the facial region using the generated facial skin mask.
-
Patent Agency Ranking
公开(公告)号：US12154379B2
公开(公告)日：2024-11-26
申请号：US18306439
申请日：2023-04-25
Applicant: Adobe Inc.
Inventor： Jinoh Oh , Xin Lu , Gahye Park , Jen-Chan Jeff Chien , Yumin Jia
Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for utilizing a machine learning model trained to determine subtle pose differentiations to analyze a repository of captured digital images of a particular user to automatically capture digital images portraying the user. For example, the disclosed systems can utilize a convolutional neural network to determine a pose/facial expression similarity metric between a sample digital image from a camera viewfinder stream of a client device and one or more previously captured digital images portraying the user. The disclosed systems can determine that the similarity metric satisfies a similarity threshold, and automatically capture a digital image utilizing a camera device of the client device. Thus, the disclosed systems can automatically and efficiently capture digital images, such as selfies, that accurately match previous digital images portraying a variety of unique facial expressions specific to individual users.
-
公开(公告)号：US11676283B2
公开(公告)日：2023-06-13
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
CPC classification number: G06T7/11 , G06T2207/20084
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.
-
公开(公告)号：US11501413B2
公开(公告)日：2022-11-15
申请号：US16950320
申请日：2020-11-17
Applicant: Adobe Inc.
Inventor： Haiting Lin , Yumin Jia , Jen-Chan Chien
Abstract: Embodiments are disclosed for generating lens blur effects. The disclosed systems and methods comprise receiving a request to apply a lens blur effect to an image, the request identifying an input image and a first disparity map, generating a plurality of disparity maps and a plurality of distance maps based on the first disparity map, splatting influences of pixels of the input image using a plurality of reshaped kernel gradients, gathering aggregations of the splatted influences, and determining a lens blur for a first pixel of the input image in an output image based on the gathered aggregations of the splatted influences.
-
公开(公告)号：US20250069437A1
公开(公告)日：2025-02-27
申请号：US18948067
申请日：2024-11-14
Applicant: Adobe Inc.
Inventor： Jinoh Oh , Xin Lu , Gahye Park , Jen-Chan Jeff Chien , Yumin Jia
Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for utilizing a machine learning model trained to determine subtle pose differentiations to analyze a repository of captured digital images of a particular user to automatically capture digital images portraying the user. For example, the disclosed systems can utilize a convolutional neural network to determine a pose/facial expression similarity metric between a sample digital image from a camera viewfinder stream of a client device and one or more previously captured digital images portraying the user. The disclosed systems can determine that the similarity metric satisfies a similarity threshold, and automatically capture a digital image utilizing a camera device of the client device. Thus, the disclosed systems can automatically and efficiently capture digital images, such as selfies, that accurately match previous digital images portraying a variety of unique facial expressions specific to individual users.
-
10.发明公开公开(公告)号：US20230260324A1
公开(公告)日：2023-08-17
申请号：US18306439
申请日：2023-04-25
Applicant: Adobe Inc.
Inventor： Jinoh Oh , Xin Lu , Gahye Park , Jen-Chan Jeff Chien , Yumin Jia
CPC classification number: G06V40/174 , G06T7/97 , G06V40/23 , G06F18/22 , G06T2207/20084
Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods for utilizing a machine learning model trained to determine subtle pose differentiations to analyze a repository of captured digital images of a particular user to automatically capture digital images portraying the user. For example, the disclosed systems can utilize a convolutional neural network to determine a pose/facial expression similarity metric between a sample digital image from a camera viewfinder stream of a client device and one or more previously captured digital images portraying the user. The disclosed systems can determine that the similarity metric satisfies a similarity threshold, and automatically capture a digital image utilizing a camera device of the client device. Thus, the disclosed systems can automatically and efficiently capture digital images, such as selfies, that accurately match previous digital images portraying a variety of unique facial expressions specific to individual users.
-
-
-
-
-
-
-
-
-
Search Results
14
records
(took 0.011 seconds)
