Generating object proposals using deep-learning models
US10496896B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 29, 2019 |
| Grant date | Dec 3, 2019 |
| Priority date | — |
| Expiry date | Mar 29, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/64
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In one embodiment, a plurality of patches of an image are processed using a first-pass of a first deep-learning model to generate object-level information for each of the patches. Each patch includes one or more pixels of the image. Using a second-pass of the first deep-learning model, a respective object proposal is generated for each of the plurality of patches of the image. The second-pass takes as input the first-pass output, and the generated respective object proposals comprise pixel-level information for each of the patches. Using a second deep-learning model, a respective score is computed for each object proposal. The second deep-learning model takes as input the first-pass output, and the object score includes a likelihood that the respective patch of the object proposal contains an entire object.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.