Invention Grant
- Patent Title: Compact language-free facial expression embedding and novel triplet training scheme
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Application No.: US16743439Application Date: 2020-01-15
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Publication No.: US11163987B2Publication Date: 2021-11-02
- Inventor: Raviteja Vemulapalli , Aseem Agarwala
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Dority & Manning, P.A.
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06N20/00 ; G06K9/46 ; G06K9/62 ; G06N3/04

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.
Public/Granted literature
- US20200151438A1 Compact Language-Free Facial Expression Embedding and Novel Triplet Training Scheme Public/Granted day:2020-05-14
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