Invention Grant
- Patent Title: Contrastive object representation learning from temporal data
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Application No.: US17681675Application Date: 2022-02-25
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Publication No.: US12149716B2Publication Date: 2024-11-19
- Inventor: Frank Brongers , Phillip Lippe , Sara Magliacane
- Applicant: QUALCOMM Technologies, Inc.
- Applicant Address: US CA San Diego
- Assignee: QUALCOMM Technologies, Inc.
- Current Assignee: QUALCOMM Technologies, Inc.
- Current Assignee Address: US CA San Diego
- Agency: QUALCOMM Technologies, Inc.
- Main IPC: H04N19/20
- IPC: H04N19/20 ; G06V10/776 ; G06V10/82 ; G06V20/40 ; H04N19/136 ; H04N19/436

Abstract:
A computer-implemented method for contrastive object representation from temporal data using an artificial neural network (ANN) includes receiving, by the ANN, a video. The video comprises a temporal sequence of frames including images of one or more objects. The ANN generates object representations corresponding to the one or more objects based on temporal data of multiple frames of the temporal sequence of frames. The object representations are communicated to a receiver.
Public/Granted literature
- US20230308666A1 CONTRASTIVE OBJECT REPRESENTATION LEARNING FROM TEMPORAL DATA Public/Granted day:2023-09-28
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