Weakly supervised natural language localization networks for video proposal prediction based on a text query
US11687588B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 5, 2019 |
| Grant date | Jun 27, 2023 |
| Priority date | — |
| Expiry date | Sep 14, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/46
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods are provided for weakly supervised natural language localization (WSNLL), for example, as implemented in a neural network or model. The WSNLL network is trained with long, untrimmed videos, i.e., videos that have not been temporally segmented or annotated. The WSNLL network or model defines or generates a video-sentence pair, which corresponds to a pairing of an untrimmed video with an input text sentence. According to some embodiments, the WSNLL network or model is implemented with a two-branch architecture, where one branch performs segment sentence alignment and the other one conducts segment selection. These methods and systems are specifically used to predict how a video proposal matches a text query using respective visual and text features.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.