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    THREE-DIMENSIONAL FACE ANIMATION FROM SPEECH
    1.
    发明公开
    THREE-DIMENSIONAL FACE ANIMATION FROM SPEECH 审中-公开

    公开(公告)号：US20230419579A1

    公开(公告)日：2023-12-28

    申请号：US18462310

    申请日：2023-09-06

    Applicant: Meta Platforms Technologies, LLC

    Inventor： Alexander Richard ,  Michael Zollhoefer ,  Fernando De la Torre ,  Yaser Sheikh

    IPC: G06T13/20 ,  G06T13/40 ,  G06T17/20 ,  G06T19/00 ,  G10L21/14

    CPC classification number: G06T13/205 ,  G06T13/40 ,  G06T17/20 ,  G06T19/006 ,  G10L21/14 ,  G10L2021/105

    Abstract: A method for training a three-dimensional model face animation model from speech, is provided. The method includes determining a first correlation value for a facial feature based on an audio waveform from a first subject, generating a first mesh for a lower portion of a human face, based on the facial feature and the first correlation value, updating the first correlation value when a difference between the first mesh and a ground truth image of the first subject is greater than a pre-selected threshold, and providing a three-dimensional model of the human face animated by speech to an immersive reality application accessed by a client device based on the difference between the first mesh and the ground truth image of the first subject. A non-transitory, computer-readable medium storing instructions to cause a system to perform the above method, and the system, are also provided.

    MIXTURE OF VOLUMETRIC PRIMITIVES FOR EFFICIENT NEURAL RENDERING
    3.
    发明公开
    MIXTURE OF VOLUMETRIC PRIMITIVES FOR EFFICIENT NEURAL RENDERING 审中-公开

    公开(公告)号：US20240303951A1

    公开(公告)日：2024-09-12

    申请号：US18636687

    申请日：2024-04-16

    Applicant: Meta Platforms Technologies, LLC

    Inventor： Stephen Anthony Lombardi ,  Tomas Simon Kreuz ,  Jason Saragih ,  Gabriel Bailowitz Schwartz ,  Michael Zollhoefer ,  Yaser Sheikh

    IPC: G06T19/20 ,  G06T15/06 ,  G06T17/20

    CPC classification number: G06T19/20 ,  G06T15/06 ,  G06T17/20 ,  G06T2219/2012

    Abstract: A method for training a real-time, modeling for animating an avatar for a subject is provided. The method includes collecting multiple images of a subject. The method also includes selecting a plurality of vertex positions in a guide mesh, indicative of a volumetric primitive enveloping the subject, determining a geometric attribute for the volumetric primitive including a position, a rotation, and a scale factor of the volumetric primitive, determining a payload attribute for each of the volumetric primitive, the payload attribute including a color value and an opacity value for each voxel in a voxel grid defining the volumetric primitive, determining a loss factor for each point in the volumetric primitive based on the geometric attribute, the payload attribute and a ground truth value, and updating a three-dimensional model for the subject. A system and a non-transitory, computer-readable medium storing instructions to perform the above method are also provided.

    THREE-DIMENSIONAL FACE ANIMATION FROM SPEECH
    4.
    发明申请
    THREE-DIMENSIONAL FACE ANIMATION FROM SPEECH 有权

    公开(公告)号：US20250131631A1

    公开(公告)日：2025-04-24

    申请号：US18914741

    申请日：2024-10-14

    Applicant: Meta Platforms Technologies, LLC

    Inventor： Alexander Richard ,  Michael Zollhoefer ,  Fernando De la Torre ,  Yaser Sheikh

    IPC: G06T13/20 ,  G06T13/40 ,  G06T17/20 ,  G06T19/00 ,  G10L21/10 ,  G10L21/14

    Abstract: A method for training a three-dimensional model face animation model from speech, is provided. The method includes determining a first correlation value for a facial feature based on an audio waveform from a first subject, generating a first mesh for a lower portion of a human face, based on the facial feature and the first correlation value, updating the first correlation value when a difference between the first mesh and a ground truth image of the first subject is greater than a pre-selected threshold, and providing a three-dimensional model of the human face animated by speech to an immersive reality application accessed by a client device based on the difference between the first mesh and the ground truth image of the first subject. A non-transitory, computer-readable medium storing instructions to cause a system to perform the above method, and the system, are also provided.

    Three-dimensional face animation from speech
    6.
    发明授权
    Three-dimensional face animation from speech 有权

    公开(公告)号：US12159339B2

    公开(公告)日：2024-12-03

    申请号：US18462310

    申请日：2023-09-06

    Applicant: Meta Platforms Technologies, LLC

    Inventor： Alexander Richard ,  Michael Zollhoefer ,  Fernando De la Torre ,  Yaser Sheikh

    IPC: G06T19/00 ,  G06T13/20 ,  G06T13/40 ,  G06T17/20 ,  G10L21/14 ,  G10L21/10

    Abstract: A method for training a three-dimensional model face animation model from speech, is provided. The method includes determining a first correlation value for a facial feature based on an audio waveform from a first subject, generating a first mesh for a lower portion of a human face, based on the facial feature and the first correlation value, updating the first correlation value when a difference between the first mesh and a ground truth image of the first subject is greater than a pre-selected threshold, and providing a three-dimensional model of the human face animated by speech to an immersive reality application accessed by a client device based on the difference between the first mesh and the ground truth image of the first subject. A non-transitory, computer-readable medium storing instructions to cause a system to perform the above method, and the system, are also provided.

    Neural 3D video synthesis
    9.
    发明授权
    Neural 3D video synthesis 有权

    公开(公告)号：US12243273B2

    公开(公告)日：2025-03-04

    申请号：US17571285

    申请日：2022-01-07

    Applicant: META PLATFORMS TECHNOLOGIES, LLC

    Inventor： Zhaoyang Lv ,  Miroslava Slavcheva ,  Tianye Li ,  Michael Zollhoefer ,  Simon Gareth Green ,  Tanner Schmidt ,  Michael Goesele ,  Steven John Lovegrove ,  Christoph Lassner ,  Changil Kim

    IPC: G06T7/00

    Abstract: In one embodiment, a method includes initializing latent codes respectively associated with times associated with frames in a training video of a scene captured by a camera. For each of the frames, a system (1) generates rendered pixel values for a set of pixels in the frame by querying NeRF using the latent code associated with the frame, a camera viewpoint associated with the frame, and ray directions associated with the set of pixels, and (2) updates the latent code associated with the frame and the NeRF based on comparisons between the rendered pixel values and original pixel values for the set of pixels. Once trained, the system renders output frames for an output video of the scene, wherein each output frame is rendered by querying the updated NeRF using one of the updated latent codes corresponding to a desired time associated with the output frame.

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