Method and system for self-supervised learning of pillar motion for autonomous driving
US11868438B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 15, 2021 |
| Grant date | Jan 9, 2024 |
| Priority date | — |
| Expiry date | Apr 13, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/10028
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method and a device for self-supervised learning, a storage medium, and an electronic device are provided. The method includes: organizing real points in one column along a vertical direction into a pillar; determining a predicted point in a next frame; determining a first loss term based on a minimum distance among distances between predicted points in the next frame and real points in the next frame, and generating a loss function including the first loss term; and performing self-supervised learning processing based on the loss function. A pillar motion parameter representing motion of a real point is determined with the pillar as a unit, so as to enhance correlation between point clouds. Self-supervised learning can be realized in a case of no precise correspondence between the predicted point and the real point, and training is performed based on a large number of unlabeled point clouds.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.