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公开(公告)号：US20230410505A1
公开(公告)日：2023-12-21
申请号：US17845353
申请日：2022-06-21
Applicant: Adobe Inc.
Inventor： Ritwik Sinha , Viswanathan Swaminathan , Trisha Mittal , John Philip Collomosse
CPC classification number: G06V20/41 , G06V20/44 , G06T7/0002
Abstract: Techniques for video manipulation detection are described to detect one or more manipulations present in digital content such as a digital video. A detection system, for instance, receives a frame of a digital video that depicts at least one entity. Coordinates of the frame that correspond to a gaze location of the entity are determined, and the detection system determines whether the coordinates correspond to a portion of an object depicted in the frame to calculate a gaze confidence score. A manipulation score is generated that indicates whether the digital video has been manipulated based on the gaze confidence score. In some examples, the manipulation score is based on at least one additional confidence score.
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公开(公告)号：US20230139824A1
公开(公告)日：2023-05-04
申请号：US17519311
申请日：2021-11-04
Applicant: ADOBE INC.
Inventor： Trisha Mittal , Viswanathan Swaminathan , Ritwik Sinha , Saayan Mitra , David Arbour , Somdeb Sarkhel
Abstract: Various disclosed embodiments are directed to using one or more algorithms or models to select a suitable or optimal variation, among multiple variations, of a given content item based on feedback. Such feedback guides the algorithm or model to arrive at suitable variation result such that the variation result is produced as the output for consumption by users. Further, various embodiments resolve tedious manual user input requirements and reduce computing resource consumption, among other things, as described in more detail below.
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公开(公告)号：US12248949B2
公开(公告)日：2025-03-11
申请号：US17519311
申请日：2021-11-04
Applicant: ADOBE INC.
Inventor： Trisha Mittal , Viswanathan Swaminathan , Ritwik Sinha , Saayan Mitra , David Arbour , Somdeb Sarkhel
IPC: G06Q30/0201 , G06N20/00
Abstract: Various disclosed embodiments are directed to using one or more algorithms or models to select a suitable or optimal variation, among multiple variations, of a given content item based on feedback. Such feedback guides the algorithm or model to arrive at suitable variation result such that the variation result is produced as the output for consumption by users. Further, various embodiments resolve tedious manual user input requirements and reduce computing resource consumption, among other things, as described in more detail below.
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