Unsupervised real-to-virtual domain unification for end-to-end highway driving
US11543830B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 24, 2018 |
| Grant date | Jan 3, 2023 |
| Priority date | — |
| Expiry date | Oct 9, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/588
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An unsupervised real to virtual domain unification model for highway driving, or DU-drive, employs a conditional generative adversarial network to transform driving images in a real domain to their canonical representations in the virtual domain, from which vehicle control commands are predicted. In the case where there are multiple real datasets, a real-to-virtual generator may be independently trained for each real domain and a global predictor could be trained with data from multiple real domains. Qualitative experiment results show this model can effectively transform real images to the virtual domain while only keeping the minimal sufficient information, and quantitative results verify that such canonical representation can eliminate domain shift and boost the performance of control command prediction task.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.