INTELLIGENT VIDEO REFRAMING
    2.
    发明申请

    公开(公告)号:US20200304754A1

    公开(公告)日:2020-09-24

    申请号:US16359876

    申请日:2019-03-20

    Applicant: ADOBE INC.

    Abstract: Embodiments of the present invention are directed towards reframing videos from one aspect ratio to another aspect ratio while maintaining visibility of regions of interest. A set of regions of interest are determined in frames in a video with a first aspect ratio. The set of regions of interest can be used to estimate an initial camera path. An optimal camera path is determined by leveraging the identified regions of interest using the initial camera path. Sub crops with a second aspect ratio different from the first aspect ratio of the video are identified. The sub crops are placed as designated using the optimal camera path to generate a cropped video with the second aspect ratio.

    Brand safety in video content
    3.
    发明授权

    公开(公告)号:US10733452B2

    公开(公告)日:2020-08-04

    申请号:US16201819

    申请日:2018-11-27

    Applicant: Adobe Inc.

    Abstract: Disclosed herein are techniques for determining brand safety of a video including image frames and audio content. In some embodiments, frame-level features, scene-level features, and video-level features are extracted by a set of frame-level models, a set of scene-level models, and a set of video-level models, respectively. Outputs from lower level models are used as inputs for higher level models. A brand safety score indicating whether it is safe to associate a brand with the video is determined based on the outputs from the set of video-level models. In some embodiments, commercial content associated with the brand is insert into the video that is determined to be safe for the brand.

    EFFICIENTLY INFERENCING DIGITAL VIDEOS UTILIZING MACHINE-LEARNING MODELS

    公开(公告)号:US20240362506A1

    公开(公告)日:2024-10-31

    申请号:US18771409

    申请日:2024-07-12

    Applicant: Adobe Inc.

    CPC classification number: G06N5/04 G06N20/00 G06T1/20 G06T3/40 G06V20/49 H04N19/13

    Abstract: This disclosure describes one or more implementations of a video inference system that utilizes machine-learning models to efficiently and flexibly process digital videos utilizing various improved video inference architectures. For example, the video inference system provides a framework for improving digital video processing by increasing the efficiency of both central processing units (CPUs) and graphics processing units (GPUs). In one example, the video inference system utilizes a first video inference architecture to reduce the number of computing resources needed to inference digital videos by analyzing multiple digital videos utilizing sets of CPU/GPU containers along with parallel pipeline processing. In a further example, the video inference system utilizes a second video inference architecture that facilitates multiple CPUs to preprocess multiple digital videos in parallel as well as a GPU to continuously, sequentially, and efficiently inference each of the digital videos.

    Intelligent video reframing
    5.
    发明授权

    公开(公告)号:US11490048B2

    公开(公告)日:2022-11-01

    申请号:US17217951

    申请日:2021-03-30

    Applicant: Adobe Inc.

    Abstract: Embodiments of the present invention are directed towards reframing videos from one aspect ratio to another aspect ratio while maintaining visibility of regions of interest. A set of regions of interest are determined in frames in a video with a first aspect ratio. The set of regions of interest can be used to estimate an initial camera path. An optimal camera path is determined by leveraging the identified regions of interest using the initial camera path. Sub crops with a second aspect ratio different from the first aspect ratio of the video are identified. The sub crops are placed as designated using the optimal camera path to generate a cropped video with the second aspect ratio.

    INCREASING EFFICIENCY OF INFERENCING DIGITAL VIDEOS UTILIZING MACHINE-LEARNING MODELS

    公开(公告)号:US20220138596A1

    公开(公告)日:2022-05-05

    申请号:US17087116

    申请日:2020-11-02

    Applicant: Adobe Inc.

    Abstract: This disclosure describes one or more implementations of a video inference system that utilizes machine-learning models to efficiently and flexibly process digital videos utilizing various improved video inference architectures. For example, the video inference system provides a framework for improving digital video processing by increasing the efficiency of both central processing units (CPUs) and graphics processing units (GPUs). In one example, the video inference system utilizes a first video inference architecture to reduce the number of computing resources needed to inference digital videos by analyzing multiple digital videos utilizing sets of CPU/GPU containers along with parallel pipeline processing. In a further example, the video inference system utilizes a second video inference architecture that facilitates multiple CPUs to preprocess multiple digital videos in parallel as well as a GPU to continuously, sequentially, and efficiently inference each of the digital videos.

    Logo detection
    7.
    发明授权

    公开(公告)号:US10936911B2

    公开(公告)日:2021-03-02

    申请号:US16937837

    申请日:2020-07-24

    Applicant: Adobe Inc.

    Abstract: Disclosed herein are techniques for detecting logos in images or video. In one embodiment, one or more candidate regions are detected for determining logos in an image. A logo is determined to be the logo in the candidate region based on matching a feature vector of a candidate region to a feature vector of the logo.

    Increasing efficiency of inferencing digital videos utilizing machine-learning models

    公开(公告)号:US12067499B2

    公开(公告)日:2024-08-20

    申请号:US17087116

    申请日:2020-11-02

    Applicant: Adobe Inc.

    CPC classification number: G06N5/04 G06N20/00 G06T1/20 G06T3/40 G06V20/49 H04N19/13

    Abstract: This disclosure describes one or more implementations of a video inference system that utilizes machine-learning models to efficiently and flexibly process digital videos utilizing various improved video inference architectures. For example, the video inference system provides a framework for improving digital video processing by increasing the efficiency of both central processing units (CPUs) and graphics processing units (GPUs). In one example, the video inference system utilizes a first video inference architecture to reduce the number of computing resources needed to inference digital videos by analyzing multiple digital videos utilizing sets of CPU/GPU containers along with parallel pipeline processing. In a further example, the video inference system utilizes a second video inference architecture that facilitates multiple CPUs to preprocess multiple digital videos in parallel as well as a GPU to continuously, sequentially, and efficiently inference each of the digital videos.

    INTELLIGENT VIDEO REFRAMING
    9.
    发明申请

    公开(公告)号:US20210218929A1

    公开(公告)日:2021-07-15

    申请号:US17217951

    申请日:2021-03-30

    Applicant: Adobe Inc.

    Abstract: Embodiments of the present invention are directed towards reframing videos from one aspect ratio to another aspect ratio while maintaining visibility of regions of interest. A set of regions of interest are determined in frames in a video with a first aspect ratio. The set of regions of interest can be used to estimate an initial camera path. An optimal camera path is determined by leveraging the identified regions of interest using the initial camera path. Sub crops with a second aspect ratio different from the first aspect ratio of the video are identified. The sub crops are placed as designated using the optimal camera path to generate a cropped video with the second aspect ratio.

    Intelligent video reframing
    10.
    发明授权

    公开(公告)号:US10986308B2

    公开(公告)日:2021-04-20

    申请号:US16359876

    申请日:2019-03-20

    Applicant: ADOBE INC.

    Abstract: Embodiments of the present invention are directed towards reframing videos from one aspect ratio to another aspect ratio while maintaining visibility of regions of interest. A set of regions of interest are determined in frames in a video with a first aspect ratio. The set of regions of interest can be used to estimate an initial camera path. An optimal camera path is determined by leveraging the identified regions of interest using the initial camera path. Sub crops with a second aspect ratio different from the first aspect ratio of the video are identified. The sub crops are placed as designated using the optimal camera path to generate a cropped video with the second aspect ratio.

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