Performing point cloud tasks using multi-scale features generated through self-attention
US12315083B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 13, 2023 |
| Grant date | May 27, 2025 |
| Priority date | — |
| Expiry date | Aug 29, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2210/56
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and apparatus for processing point clouds using neural networks to perform a machine learning task. In one aspect, a system comprises one or more computers configured to obtain a set of point clouds captured by one or more sensors. Each point cloud includes a respective plurality of three-dimensional points. The one or more computers assign the three-dimensional points to respective voxels in a voxel grid, where the grid of voxels includes non-empty voxels to which one or more points are assigned and empty voxels to which no points are assigned. For each non-empty voxel, the one or more computers generate initial features based on the points that are assigned to the non-empty voxel. The one or more computers generate multi-scale features of the voxel grid, and the one or more computers generate an output for a point cloud processing task using the multi-scale features of the voxel grid.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.