Object detection network and method
US11462029B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 7, 2020 |
| Grant date | Oct 4, 2022 |
| Priority date | — |
| Expiry date | Dec 11, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/58
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An object detection network includes: a hybrid voxel feature extractor configured to acquire a raw point cloud, extract a hybrid scale voxel feature from the raw point cloud, and project the hybrid scale voxel feature to generate a pseudo-image feature map; a backbone network configured to perform a hybrid voxel scale feature fusion by using the pseudo-image feature map to generate multi-class pyramid features; and a detection head configured to predict a three-dimensional object box of a corresponding class according to the multi-class pyramid features. The object detection network can effectively solve a problem that under a single voxel scale, inference time is longer if the voxel scale is smaller, and an intricate feature cannot be captured and a smaller object cannot be accurately located if the voxel scale is larger. Different classes of 3D objects can be detected quickly and accurately in a 3D scene.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.