Systems and methods of contrastive point completion with fine-to-coarse refinement
US11587291B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 30, 2021 |
| Grant date | Feb 21, 2023 |
| Priority date | — |
| Expiry date | Jun 30, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2219/2024
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An electronic apparatus performs a method of recovering a complete and dense point cloud from a partial point cloud. The method includes: constructing a sparse but complete point cloud from the partial point cloud through a contrastive teacher-student neural network; and transforming the sparse but complete point cloud to the complete and dense point cloud. In some embodiments, the contrastive teacher-student neural network has a dual network structure comprising a teacher network and a student network both sharing the same architecture. The teacher network is a point cloud self-reconstruction network, and the student network is a point cloud completion network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.