Invention Grant
- Patent Title: Equivariant models for generating vector representations of temporally-varying content
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Application No.: US17466636Application Date: 2021-09-03
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Publication No.: US12061668B2Publication Date: 2024-08-13
- Inventor: Simon Jenni , Hailin Jin
- Applicant: ADOBE INC.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: Shook, Hardy & Bacon L.L.P.
- Main IPC: G06F18/213
- IPC: G06F18/213 ; G06F18/214 ; G06F18/2413 ; G06N3/045 ; G06N3/08

Abstract:
The disclosed invention includes systems and methods for training and employing equivariant models for generating representations (e.g., vector representations) of temporally-varying content, such as but not limited to video content. The trained models are equivariant to temporal transformations applied to the input content (e.g., video content). The trained models are additionally invariant to non-temporal transformations (e.g., spatial and/or color-space transformations) applied to the input content. Such representations are employed in various machine learning tasks, such as but not limited to video retrieval (e.g., video search engine applications), identification of actions depicted in video, and temporally ordering clips of the video.
Public/Granted literature
- US20230075087A1 EQUIVARIANT MODELS FOR GENERATING VECTOR REPRESENTATIONS OF TEMPORALLY-VARYING CONTENT Public/Granted day:2023-03-09
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