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    Style-aware audio-driven talking head animation from a single image
    2.
    发明授权
    Style-aware audio-driven talking head animation from a single image 有权

    公开(公告)号：US11776188B2

    公开(公告)日：2023-10-03

    申请号：US17887685

    申请日：2022-08-15

    Applicant: Adobe Inc.

    Inventor： Dingzeyu Li ,  Yang Zhou ,  Jose Ignacio Echevarria Vallespi ,  Elya Shechtman

    IPC: G06T13/20 ,  G06T17/20 ,  G06T13/40

    CPC classification number: G06T13/205 ,  G06T13/40 ,  G06T17/20

    Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for generating an animation of a talking head from an input audio signal of speech and a representation (such as a static image) of a head to animate. Generally, a neural network can learn to predict a set of 3D facial landmarks that can be used to drive the animation. In some embodiments, the neural network can learn to detect different speaking styles in the input speech and account for the different speaking styles when predicting the 3D facial landmarks. Generally, template 3D facial landmarks can be identified or extracted from the input image or other representation of the head, and the template 3D facial landmarks can be used with successive windows of audio from the input speech to predict 3D facial landmarks and generate a corresponding animation with plausible 3D effects.

    Interacting with hierarchical clusters of video segments using a video timeline
    3.
    发明授权
    Interacting with hierarchical clusters of video segments using a video timeline 有权

    公开(公告)号：US11630562B2

    公开(公告)日：2023-04-18

    申请号：US17017366

    申请日：2020-09-10

    Applicant: ADOBE INC.

    Inventor： Seth Walker ,  Joy Oakyung Kim ,  Aseem Agarwala ,  Joel R. Brandt ,  Jovan Popović ,  Lubomira Dontcheva ,  Dingzeyu Li ,  Hijung Shin ,  Xue Bai

    IPC: G06F3/04847 ,  G06F3/04845 ,  G06F3/0485

    Abstract: Embodiments are directed to techniques for interacting with a hierarchical video segmentation using a video timeline. In some embodiments, the finest level of a hierarchical segmentation identifies the smallest interaction unit of a video—semantically defined video segments of unequal duration called clip atoms, and higher levels cluster the clip atoms into coarser sets of video segments. A presented video timeline is segmented based on one of the levels, and one or more segments are selected through interactions with the video timeline. For example, a click or tap on a video segment or a drag operation dragging along the timeline snaps selection boundaries to corresponding segment boundaries defined by the level. Navigating to a different level of the hierarchy transforms the selection into coarser or finer video segments defined by the level. Any operation can be performed on selected video segments, including playing back, trimming, or editing.

    RENDERING SCENE-AWARE AUDIO USING NEURAL NETWORK-BASED ACOUSTIC ANALYSIS
    4.
    发明申请
    RENDERING SCENE-AWARE AUDIO USING NEURAL NETWORK-BASED ACOUSTIC ANALYSIS 有权

    公开(公告)号：US20210136510A1

    公开(公告)日：2021-05-06

    申请号：US16674924

    申请日：2019-11-05

    Applicant: Adobe Inc.

    Inventor： Zhenyu Tang ,  Timothy Langlois ,  Nicholas Bryan ,  Dingzeyu Li

    IPC: H04S7/00 ,  G06N3/04 ,  G06N3/08

    Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for rendering scene-aware audio based on acoustic properties of a user environment. For example, the disclosed system can use neural networks to analyze an audio recording to predict environment equalizations and reverberation decay times of the user environment without using a captured impulse response of the user environment. Additionally, the disclosed system can use the predicted reverberation decay times with an audio simulation of the user environment to optimize material parameters for the user environment. The disclosed system can then generate an audio sample that includes scene-aware acoustic properties based on the predicted environment equalizations, material parameters, and an environment geometry of the user environment. Furthermore, the disclosed system can augment training data for training the neural networks using frequency-dependent equalization information associated with measured and synthetic impulse responses.

    Interacting with hierarchical clusters of video segments using a metadata panel
    5.
    发明授权
    Interacting with hierarchical clusters of video segments using a metadata panel 有权

    公开(公告)号：US11995894B2

    公开(公告)日：2024-05-28

    申请号：US17017353

    申请日：2020-09-10

    Applicant: ADOBE INC.

    Inventor： Seth Walker ,  Joy Oakyung Kim ,  Hijung Shin ,  Aseem Agarwala ,  Joel R. Brandt ,  Jovan Popović ,  Lubomira Dontcheva ,  Dingzeyu Li ,  Xue Bai

    IPC: G06V20/40 ,  G06T7/10

    CPC classification number: G06V20/49 ,  G06T7/10 ,  G06V20/41 ,  G06T2207/10016

    Abstract: Embodiments are directed to techniques for interacting with a hierarchical video segmentation using a metadata panel with a composite list of video metadata. The composite list is segmented into selectable metadata segments at locations corresponding to boundaries of video segments defined by a hierarchical segmentation. In some embodiments, the finest level of a hierarchical segmentation identifies the smallest interaction unit of a video—semantically defined video segments of unequal duration called clip atoms, and higher levels cluster the clip atoms into coarser sets of video segments. One or more metadata segments can be selected in various ways, such as by clicking or tapping on a metadata segment or by performing a metadata search. When a metadata segment is selected, a corresponding video segment is emphasized on the video timeline, a playback cursor is moved to the first video frame of the video segment, and the first video frame is presented.

    Generating scene-aware audio using a neural network-based acoustic analysis
    6.
    发明授权
    Generating scene-aware audio using a neural network-based acoustic analysis 有权

    公开(公告)号：US11812254B2

    公开(公告)日：2023-11-07

    申请号：US17515918

    申请日：2021-11-01

    Applicant: Adobe Inc.

    Inventor： Zhenyu Tang ,  Timothy Langlois ,  Nicholas Bryan ,  Dingzeyu Li

    IPC: H04S7/00 ,  G06N3/08 ,  G06N3/04

    CPC classification number: H04S7/305 ,  G06N3/04 ,  G06N3/08 ,  H04S7/307 ,  H04S2400/11

    Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for rendering scene-aware audio based on acoustic properties of a user environment. For example, the disclosed system can use neural networks to analyze an audio recording to predict environment equalizations and reverberation decay times of the user environment without using a captured impulse response of the user environment. Additionally, the disclosed system can use the predicted reverberation decay times with an audio simulation of the user environment to optimize material parameters for the user environment. The disclosed system can then generate an audio sample that includes scene-aware acoustic properties based on the predicted environment equalizations, material parameters, and an environment geometry of the user environment. Furthermore, the disclosed system can augment training data for training the neural networks using frequency-dependent equalization information associated with measured and synthetic impulse responses.

    STYLE-AWARE AUDIO-DRIVEN TALKING HEAD ANIMATION FROM A SINGLE IMAGE
    7.
    发明申请
    STYLE-AWARE AUDIO-DRIVEN TALKING HEAD ANIMATION FROM A SINGLE IMAGE 有权

    公开(公告)号：US20220392131A1

    公开(公告)日：2022-12-08

    申请号：US17887685

    申请日：2022-08-15

    Applicant: Adobe Inc.

    Inventor： Dingzeyu Li ,  Yang Zhou ,  Jose Ignacio Echevarria Vallespi ,  Elya Shechtman

    IPC: G06T13/20 ,  G06T17/20 ,  G06T13/40

    Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for generating an animation of a talking head from an input audio signal of speech and a representation (such as a static image) of a head to animate. Generally, a neural network can learn to predict a set of 3D facial landmarks that can be used to drive the animation. In some embodiments, the neural network can learn to detect different speaking styles in the input speech and account for the different speaking styles when predicting the 3D facial landmarks. Generally, template 3D facial landmarks can be identified or extracted from the input image or other representation of the head, and the template 3D facial landmarks can be used with successive windows of audio from the input speech to predict 3D facial landmarks and generate a corresponding animation with plausible 3D effects.

    Segmentation and hierarchical clustering of video
    8.
    发明授权
    Segmentation and hierarchical clustering of video 有权

    公开(公告)号：US11450112B2

    公开(公告)日：2022-09-20

    申请号：US17017344

    申请日：2020-09-10

    Applicant: ADOBE INC.

    Inventor： Hijung Shin ,  Xue Bai ,  Aseem Agarwala ,  Joel R. Brandt ,  Jovan Popović ,  Lubomira Dontcheva ,  Dingzeyu Li ,  Joy Oakyung Kim ,  Seth Walker

    IPC: G11B27/00 ,  G11B27/19 ,  G06V20/40 ,  G06K9/62 ,  G10L25/78 ,  H04N7/00 ,  H04N21/00

    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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