Invention Grant
- Patent Title: Classifying a video stream using a self-attention-based machine-learning model
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Application No.: US17461755Application Date: 2021-08-30
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Publication No.: US12080067B2Publication Date: 2024-09-03
- Inventor: Gediminas Bertasius , Heng Wang , Lorenzo Torresani
- Applicant: Meta Platforms, Inc.
- Applicant Address: US CA Menlo Park
- Assignee: Meta Platforms, Inc.
- Current Assignee: Meta Platforms, Inc.
- Current Assignee Address: US CA Menlo Park
- Agency: BakerHostetler
- Main IPC: G06V10/50
- IPC: G06V10/50 ; G06F18/21 ; G06N3/045 ; G06N3/08 ; G06N20/00 ; G06V10/56 ; G06V10/75 ; G06V10/82 ; G06V20/40

Abstract:
In one embodiment, a method includes accessing a stream of F video frames, where each of the F video frames includes N patches that are non-overlapping, generating an initial embedding vector for each of the N×F patches in the F video frames, generating a classification embedding by processing the generated N×F initial embedding vectors using a self-attention-based machine-learning model that computes a temporal attention and a spatial attention for each of the N×F patches, and determining a class of the stream of video frames based on the generated classification embedding.
Public/Granted literature
- US20220253633A1 CLASSIFYING A VIDEO STREAM USING A SELF-ATTENTION-BASED MACHINE-LEARNING MODEL Public/Granted day:2022-08-11
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