Knowledge Commons of Institute of Automation,CAS
Superpoint-guided Semi-supervised Semantic Segmentation of 3D Point Clouds | |
Deng, Shuang1,2,3; Dong, Qiulei1,2,3; Liu, Bo1,4; Hu, Zhanyi1,4 | |
2022-07 | |
会议名称 | IEEE Conference on Robotics and Automation (ICRA) |
会议日期 | 2022-5 |
会议地点 | Philadelphia, USA |
摘要 | 3D point cloud semantic segmentation is a challenging topic in the computer vision field. Most of the existing methods in literature require a large amount of fully labeled training data, but it is extremely time-consuming to obtain these training data by manually labeling massive point clouds. Addressing this problem, we propose a superpoint-guided semi-supervised segmentation network for 3D point clouds, which jointly utilizes a small portion of labeled scene point clouds and a large number of unlabeled point clouds for network training. The proposed network is iteratively updated with its predicted pseudo labels, where a superpoint generation module is introduced for extracting superpoints from 3D point clouds, and a pseudo-label optimization module is explored for automatically assigning pseudo labels to the unlabeled points under the constraint of the extracted superpoints. Additionally, there are some 3D points without pseudo-label supervision. We propose an edge prediction module to constrain features of edge points. A superpoint feature aggregation module and a superpoint feature consistency loss function are introduced to smooth superpoint features. Extensive experimental results on two 3D public datasets demonstrate that our method can achieve better performance than several state-of-the-art point cloud segmentation networks and several popular semi-supervised segmentation methods with few labeled scenes. |
收录类别 | EI |
七大方向——子方向分类 | 三维视觉 |
国重实验室规划方向分类 | 其他 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/49906 |
专题 | 多模态人工智能系统全国重点实验室_机器人视觉 |
通讯作者 | Dong, Qiulei |
作者单位 | 1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China 2.School of Artificial Intelligence, University of Chinese Academy of Sciences, China 3.Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, China 4.School of Future Technology, University of Chinese Academy of Sciences, China |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Deng, Shuang,Dong, Qiulei,Liu, Bo,et al. Superpoint-guided Semi-supervised Semantic Segmentation of 3D Point Clouds[C],2022. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
ICRA2022.pdf(496KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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