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公开(公告)号：US12238451B2
公开(公告)日：2025-02-25
申请号：US18055301
申请日：2022-11-14
Applicant: Adobe Inc.
Inventor： Uttaran Bhattacharya , Gang Wu , Viswanathan Swaminathan , Stefano Petrangeli
Abstract: Embodiments are disclosed for predicting, using neural networks, editing operations for application to a video sequence based on processing conversational messages by a video editing system. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving an input including a video sequence and text sentences, the text sentences describing a modification to the video sequence, mapping, by a first neural network content of the text sentences describing the modification to the video sequence to a candidate editing operation, processing, by a second neural network, the video sequence to predict parameter values for the candidate editing operation, and generating a modified video sequence by applying the candidate editing operation with the predicted parameter values to the video sequence.
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公开(公告)号：US11574477B2
公开(公告)日：2023-02-07
申请号：US17194755
申请日：2021-03-08
Applicant: Adobe Inc.
Inventor： Gang Wu , Viswanathan Swaminathan , Uttaran Bhattacharya , Stefano Petrangeli
Abstract: In implementations for highlight video generated with adaptable multimodal customization, a multimodal detection system tracks activities based on poses and faces of persons depicted in video clips of video content. The system determines a pose highlight score and a face highlight score for each of the video clips that depict at least one person, the highlight scores representing a relative level of the interest in an activity depicted in a video clip. The system also determines pose-based emotion features for each of the video clips. The system can detect actions based on the activities of the persons depicted in the video clips, and detect emotions exhibited by the persons depicted in the video clips. The system can receive input selections of actions and emotions, and filter the video clips based on the selected actions and emotions. The system can then generate a highlight video of ranked and filtered video clips.
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公开(公告)号：US20220284220A1
公开(公告)日：2022-09-08
申请号：US17194755
申请日：2021-03-08
Applicant: Adobe Inc.
Inventor： Gang Wu , Viswanathan Swaminathan , Uttaran Bhattacharya , Stefano Petrangeli
Abstract: In implementations for highlight video generated with adaptable multimodal customization, a multimodal detection system tracks activities based on poses and faces of persons depicted in video clips of video content. The system determines a pose highlight score and a face highlight score for each of the video clips that depict at least one person, the highlight scores representing a relative level of the interest in an activity depicted in a video clip. The system also determines pose-based emotion features for each of the video clips. The system can detect actions based on the activities of the persons depicted in the video clips, and detect emotions exhibited by the persons depicted in the video clips. The system can receive input selections of actions and emotions, and filter the video clips based on the selected actions and emotions. The system can then generate a highlight video of ranked and filtered video clips.
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