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12.发明授权公开(公告)号：US11682238B2
公开(公告)日：2023-06-20
申请号：US17175441
申请日：2021-02-12
Applicant: Adobe Inc.
Inventor： Jimei Yang , Deepali Aneja , Dingzeyu Li , Jun Saito , Yang Zhou
IPC: G06V40/20 , G06T7/215 , G06V20/40 , G06V40/10 , H04N5/06 , H04N21/8547 , G11B27/031 , G10H1/36 , G11B27/10 , H04N21/845
CPC classification number: G06V40/23 , G06T7/215 , G06V20/41 , G06V20/46 , G06V40/103 , H04N5/06 , H04N21/8456 , H04N21/8547
Abstract: Embodiments are disclosed for re-timing a video sequence to an audio sequence based on the detection of motion beats in the video sequence and audio beats in the audio sequence. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving a first input, the first input including a video sequence, detecting motion beats in the video sequence, receiving a second input, the second input including an audio sequence, detecting audio beats in the audio sequence, modifying the video sequence by matching the detected motions beats in the video sequence to the detected audio beats in the audio sequence, and outputting the modified video sequence.
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公开(公告)号：US20220301313A1
公开(公告)日：2022-09-22
申请号：US17805076
申请日：2022-06-02
Applicant: ADOBE INC.
Inventor： Hijung Shin , Xue Bai , Aseem Agarwala , Joel R. Brandt , Jovan Popovic , Lubomira Dontcheva , Dingzeyu Li , Joy Oakyung Kim , Seth Walker
Abstract: Embodiments are directed to segmentation and hierarchical clustering of video. In an example implementation, a video is ingested to generate a multi-level hierarchical segmentation of the video. In some embodiments, the finest level identifies a smallest interaction unit of the video—semantically defined video segments of unequal duration called clip atoms. Clip atom boundaries are detected in various ways. For example, speech boundaries are detected from audio of the video, and scene boundaries are detected from video frames of the video. The detected boundaries are used to define the clip atoms, which are hierarchically clustered to form a multi-level hierarchical representation of the video. In some cases, the hierarchical segmentation identifies a static, pre-computed, hierarchical set of video segments, where each level of the hierarchical segmentation identifies a complete set (i.e., covering the entire range of the video) of disjoint (i.e., non-overlapping) video segments with a corresponding level of granularity.
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公开(公告)号：US20220292831A1
公开(公告)日：2022-09-15
申请号：US17805080
申请日：2022-06-02
Applicant: ADOBE INC.
Inventor： Hijung Shin , Xue Bai , Aseem Agarwala , Joel R. Brandt , Jovan Popovic , Lubomira Dontcheva , Dingzeyu Li , Joy Oakyung Kim , Seth Walker
Abstract: Embodiments are directed to segmentation and hierarchical clustering of video. In an example implementation, a video is ingested to generate a multi-level hierarchical segmentation of the video. In some embodiments, the finest level identifies a smallest interaction unit of the video—semantically defined video segments of unequal duration called clip atoms. Clip atom boundaries are detected in various ways. For example, speech boundaries are detected from audio of the video, and scene boundaries are detected from video frames of the video. The detected boundaries are used to define the clip atoms, which are hierarchically clustered to form a multi-level hierarchical representation of the video. In some cases, the hierarchical segmentation identifies a static, pre-computed, hierarchical set of video segments, where each level of the hierarchical segmentation identifies a complete set (i.e., covering the entire range of the video) of disjoint (i.e., non-overlapping) video segments with a corresponding level of granularity.
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公开(公告)号：US20220292830A1
公开(公告)日：2022-09-15
申请号：US17805075
申请日：2022-06-02
Applicant: ADOBE INC.
Inventor： Hijung Shin , Xue Bai , Aseem Agarwala , Joel R. Brandt , Jovan Popovic , Lubomira Dontcheva , Dingzeyu Li , Joy Oakyung Kim , Seth Walker
Abstract: Embodiments are directed to segmentation and hierarchical clustering of video. In an example implementation, a video is ingested to generate a multi-level hierarchical segmentation of the video. In some embodiments, the finest level identifies a smallest interaction unit of the video—semantically defined video segments of unequal duration called clip atoms. Clip atom boundaries are detected in various ways. For example, speech boundaries are detected from audio of the video, and scene boundaries are detected from video frames of the video. The detected boundaries are used to define the clip atoms, which are hierarchically clustered to form a multi-level hierarchical representation of the video. In some cases, the hierarchical segmentation identifies a static, pre-computed, hierarchical set of video segments, where each level of the hierarchical segmentation identifies a complete set (i.e., covering the entire range of the video) of disjoint (i.e., non-overlapping) video segments with a corresponding level of granularity.
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Patent Agency Ranking
公开(公告)号：US20220101476A1
公开(公告)日：2022-03-31
申请号：US17034467
申请日：2020-09-28
Applicant: Adobe Inc.
Inventor： Oliver Wang , Jianming Zhang , Dingzeyu Li , Zekun Hao
Abstract: The technology described herein is directed to a cross-domain training framework that iteratively trains a domain adaptive refinement agent to refine low quality real-world image acquisition data, e.g., depth maps, when accompanied by corresponding conditional data from other modalities, such as the underlying images or video from which the image acquisition data is computed. The cross-domain training framework includes a shared cross-domain encoder and two conditional decoder branch networks, e.g., a synthetic conditional depth prediction branch network and a real conditional depth prediction branch network. The shared cross-domain encoder converts synthetic and real-world image acquisition data into synthetic and real compact feature representations, respectively. The synthetic and real conditional decoder branch networks convert the respective synthetic and real compact feature representations back to synthetic and real image acquisition data (refined versions) conditioned on data from the other modalities. The cross-domain training framework iteratively trains the domain adaptive refinement agent.
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公开(公告)号：US20220076707A1
公开(公告)日：2022-03-10
申请号：US17330702
申请日：2021-05-26
Applicant: ADOBE INC.
Inventor： Seth Walker , Hijung Shin , Cristin Ailidh Fraser , Aseem Agarwala , Lubomira Dontcheva , Joel Richard Brandt , Jovan Popovic , Joy Oakyung Kim , Justin Salamon , Jui-hsien Wang , Timothy Jeewun Ganter , Xue Bai , Dingzeyu Li
IPC: G11B27/036 , G06F3/0486 , G06F3/0482
Abstract: Embodiments are directed to a snap point segmentation that defines the locations of selection snap points for a selection of video segments. Candidate snap points are determined from boundaries of feature ranges of the video indicating when instances of detected features are present in the video. In some embodiments, candidate snap point separations are penalized for being separated by less than a minimum duration corresponding to a minimum pixel separation between consecutive snap points on a video timeline. The snap point segmentation is computed by solving a shortest path problem through a graph that models different snap point locations and separations. When a user clicks or taps on the video timeline and drags, a selection snaps to the snap points defined by the snap point segmentation. In some embodiments, the snap points are displayed during a drag operation and disappear when the drag operation is released.
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公开(公告)号：US20220076706A1
公开(公告)日：2022-03-10
申请号：US17330689
申请日：2021-05-26
Applicant: ADOBE INC.
Inventor： Seth Walker , Hijung Shin , Cristin Ailidh Fraser , Aseem Agarwala , Lubomira Dontcheva , Joel Richard Brandt , Jovan Popovic , Joy Oakyung Kim , Justin Salamon , Jui-hsien Wang , Timothy Jeewun Ganter , Xue Bai , Dingzeyu Li
IPC: G11B27/036 , G06F3/0482 , G06F3/0486
Abstract: Embodiments are directed to interactive tiles that represent video segments of a segmentation of a video. In some embodiments, each interactive tile represents a different video segment from a particular video segmentation (e.g., a default video segmentation). Each interactive tile includes a thumbnail (e.g., the first frame of the video segment represented by the tile), some transcript from the beginning of the video segment, a visualization of detected faces in the video segment, and one or more faceted timelines that visualize a category of detected features (e.g., a visualization of detected visual scenes, audio classifications, visual artifacts). In some embodiments, interacting with a particular interactive tile navigates to a corresponding portion of the video, adds a corresponding video segment to a selection, and/or scrubs through tile thumbnails.
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公开(公告)号：US12033669B2
公开(公告)日：2024-07-09
申请号：US17330702
申请日：2021-05-26
Applicant: ADOBE INC.
Inventor： Seth Walker , Hijung Shin , Cristin Ailidh Fraser , Aseem Agarwala , Lubomira Dontcheva , Joel Richard Brandt , Jovan Popović , Joy Oakyung Kim , Justin Salamon , Jui-hsien Wang , Timothy Jeewun Ganter , Xue Bai , Dingzeyu Li
IPC: G11B27/00 , G06F3/0482 , G06F3/0486 , G11B27/02 , G11B27/036 , G11B27/10 , G11B27/031 , G11B27/36
CPC classification number: G11B27/036 , G06F3/0482 , G06F3/0486
Abstract: Embodiments are directed to a snap point segmentation that defines the locations of selection snap points for a selection of video segments. Candidate snap points are determined from boundaries of feature ranges of the video indicating when instances of detected features are present in the video. In some embodiments, candidate snap point separations are penalized for being separated by less than a minimum duration corresponding to a minimum pixel separation between consecutive snap points on a video timeline. The snap point segmentation is computed by solving a shortest path problem through a graph that models different snap point locations and separations. When a user clicks or taps on the video timeline and drags, a selection snaps to the snap points defined by the snap point segmentation. In some embodiments, the snap points are displayed during a drag operation and disappear when the drag operation is released.
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