Cross-Domain Few-Shot 3D Point Cloud Semantic Segmentation
文献类型：期刊论文
| 作者 | Xiao, Jiwei; Wang, Ruiping1; He, Chen; Chen, Xilin |
| 刊名 | PATTERN RECOGNITION LETTERS
 |
| 出版日期 | 2025-11-01 |
| 卷号 | 197页码:51-57 |
| 关键词 | 3D semantic segmentation Cross Domain Adaptation Few-shot learning |
| ISSN号 | 0167-8655 |
| DOI | 10.1016/j.patrec.2025.07.001 |
| 英文摘要 | Training fully supervised 3D point cloud semantic segmentation models is hindered by the need for extensive datasets and expensive annotation, limiting rapid expansion to additional categories. In response to these challenges, Few-Shot 3D Point Cloud Semantic Segmentation (3D FS-SSeg) methods utilize less labeled scene data to generalize to new categories. However, these approaches still depend on laboriously annotated semantic labels in 3D scenes. To address this limitation, we propose a more practical task named Cross-Domain Few-Shot 3D Point Cloud Semantic Segmentation (3D CD-FS-SSeg). In this task, we expand the model's ability to segment point clouds of novel classes in unknown scenes by leveraging a small amount of low-cost CAD object model data or RGB-D image data as a support set. To accomplish the above task, we propose an approach that consists of two main blocks: a Cross Domain Adaptation (CDA) module that transfers the contextual information of the query scene to the support object to reduce the cross-domain gap, and a Multiple Prototypes Discriminative (MPD) loss that enhances inter-class variation while reducing intra-class variation. Experimental results on the ScanNet and S3DIS datasets demonstrate that our proposed method provides a significant improvement on the 3D CD-FS-SSeg benchmark. |
| 资助项目 | National Key R&D Program of China[2021ZD0111901] ; National Key R&D Program of China[2023YFF1105104] ; Natural Science Foundation of China[U21B2025] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:001541029600001 |
| 出版者 | ELSEVIER |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/42008]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Wang, Ruiping |
| 作者单位 | 1.Chinese Acad Sci, Inst Comp Technol, State Key Lab AI Safety, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xiao, Jiwei,Wang, Ruiping,He, Chen,et al. Cross-Domain Few-Shot 3D Point Cloud Semantic Segmentation[J]. PATTERN RECOGNITION LETTERS,2025,197:51-57. |
| APA | Xiao, Jiwei,Wang, Ruiping,He, Chen,&Chen, Xilin.(2025).Cross-Domain Few-Shot 3D Point Cloud Semantic Segmentation.PATTERN RECOGNITION LETTERS,197,51-57. |
| MLA | Xiao, Jiwei,et al."Cross-Domain Few-Shot 3D Point Cloud Semantic Segmentation".PATTERN RECOGNITION LETTERS 197(2025):51-57. |
入库方式： OAI收割
来源：计算技术研究所
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