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公开(公告)号：US11163987B2
公开(公告)日：2021-11-02
申请号：US16743439
申请日：2020-01-15
Applicant: Google LLC
Inventor： Raviteja Vemulapalli , Aseem Agarwala
Abstract: The present disclosure provides systems and methods that include or otherwise leverage use of a facial expression model that is configured to provide a facial expression embedding. In particular, the facial expression model can receive an input image that depicts a face and, in response, provide a facial expression embedding that encodes information descriptive of a facial expression made by the face depicted in the input image. As an example, the facial expression model can be or include a neural network such as a convolutional neural network. The present disclosure also provides a novel and unique triplet training scheme which does not rely upon designation of a particular image as an anchor or reference image.
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公开(公告)号：US10812825B2
公开(公告)日：2020-10-20
申请号：US16349532
申请日：2017-09-29
Applicant: Google LLC
Inventor： Ziwei Liu , Yiming Liu , Aseem Agarwala
Abstract: The present disclosure provides systems and methods that leverage machine-learned models (e.g., neural networks) to provide video frame synthesis. In particular, the systems and methods of the present disclosure can include or otherwise leverage a machine-learned video frame synthesis model to allow for video frames to be synthesized from videos. In one particular example, the video frame synthesis model can include a convolutional neural network having a voxel flow layer and provides one or more synthesized video frames as part of slow-motion video.
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公开(公告)号：US20190289321A1
公开(公告)日：2019-09-19
申请号：US16349532
申请日：2017-09-29
Applicant: Google LLC
Inventor： Ziwei Liu , Yiming Liu , Aseem Agarwala
IPC: H04N19/587 , H04N19/89 , G06N3/08 , H04N7/01
Abstract: The present disclosure provides systems and methods that leverage machine-learned models (e.g., neural networks) to provide video frame synthesis. In particular, the systems and methods of the present disclosure can include or otherwise leverage a machine-learned video frame synthesis model to allow for video frames to be synthesized from videos. In one particular example, the video frame synthesis model can include a convolutional neural network having a voxel flow layer and provides one or more synthesized video frames as part of slow-motion video.
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公开(公告)号：US20200151438A1
公开(公告)日：2020-05-14
申请号：US16743439
申请日：2020-01-15
Applicant: Google LLC
Inventor： Raviteja Vemulapalli , Aseem Agarwala
Abstract: The present disclosure provides systems and methods that include or otherwise leverage use of a facial expression model that is configured to provide a facial expression embedding. In particular, the facial expression model can receive an input image that depicts a face and, in response, provide a facial expression embedding that encodes information descriptive of a facial expression made by the face depicted in the input image. As an example, the facial expression model can be or include a neural network such as a convolutional neural network. The present disclosure also provides a novel and unique triplet training scheme which does not rely upon designation of a particular image as an anchor or reference image.
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