Title:
NETWORK OPTIMIZATION STRUCTURE EMPLOYING 3D TARGET CLASSIFICATION AND SCENE SEMANTIC SEGMENTATION
Document Type and Number:
WIPO Patent Application WO/2020/119619
Kind Code:
A1
Abstract:
A network structure optimization method employing 3D target classification and scene semantic segmentation, relating to the field of robots and the field of reinforcement learning. The method comprises: after acquiring the features of points, scoring each of the points, the level of the score representing the contribution of the point to a task; and sorting the scores, and selecting the top N points. In center point sampling, all of acquired point sets are subsets of point sets in a previous layer, and thus, the same point has different features in the same layer. Thus, when feature extraction is performed on the next layer, different features located in the same point in the previous layer can be combined, and the combination technique combines fine-grained features of a specified point. The method improves the classification performance of PointNet++ for objects, and improves performance for scene segmentation.
More Like This:
| JPS6029883 | OPTICAL CHARACTER READER |
| JPH07182456 | CHARACTER INPUT DEVICE |
| WO/2018/000038 | SYSTEM AND METHOD FOR IDENTIFYING A CAMERA POSE OF A FORWARD FACING CAMERA IN A VEHICLE |
Inventors:
CHENG JUN (CN)
ZHANG QIESHI (CN)
WANG SHENGWEN (CN)
ZHANG QIESHI (CN)
WANG SHENGWEN (CN)
Application Number:
PCT/CN2019/123947
Publication Date:
June 18, 2020
Filing Date:
December 09, 2019
Export Citation:
Assignee:
SHENZHEN INST OF ADV TECH CAS (CN)
International Classes:
G06K9/62
Foreign References:
| CN109753995A | 2019-05-14 | |||
| CN108564097A | 2018-09-21 | |||
| CN108345887A | 2018-07-31 | |||
| CN108509949A | 2018-09-07 |
Other References:
QI, CHARLES R. ET AL.: "PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space,", 31ST CONFERENCE ON NEURAL INFORMATION PROCESSING SYSTEMS,, 31 December 2017 (2017-12-31), XP055713540, DOI: 20200218090554A
Attorney, Agent or Firm:
BEIJING CHENGHUI LAW FIRM (CN)
Download PDF: