Switchable propagation neural network
US11328173B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 27, 2020 |
| Grant date | May 10, 2022 |
| Priority date | — |
| Expiry date | Feb 6, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20208
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A temporal propagation network (TPN) system learns the affinity matrix for video image processing tasks. An affinity matrix is a generic matrix that defines the similarity of two points in space. The TPN system includes a guidance neural network model and a temporal propagation module and is trained for a particular computer vision task to propagate visual properties from a key-frame represented by dense data (color), to another frame that is represented by coarse data (grey-scale). The guidance neural network model generates an affinity matrix referred to as a global transformation matrix from task-specific data for the key-frame and the other frame. The temporal propagation module applies the global transformation matrix to the key-frame property data to produce propagated property data (color) for the other frame. For example, the TPN system may be used to colorize several frames of greyscale video using a single manually colorized key-frame.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.