Method, apparatus and system for adaptating a machine learning model for optical flow map prediction
US12354284B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 11, 2021 |
| Grant date | Jul 8, 2025 |
| Priority date | — |
| Expiry date | Jan 11, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
There is provided a method, apparatus and system for adapting a machine learning model for optical flow prediction. A machine learning model can be trained or adapted based on compressed video data, using motion vector information extracted from the compressed video data as ground-truth information for use in adapting the model to a motion vector prediction task. The model so adapted can accordingly be adapted for the similar task of optical flow prediction. Thus, the model can be adapted at test time to image data which is taken from an appropriate distribution. A meta-learning process can be performed prior to such model adaptation to potentially improve the model's performance.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.