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Data-efficient 3D instance segmentation by transferring knowledge from synthetic scans

文献类型：期刊论文

作者Wu, Xiaodong2; Wang, Ruiping2; Chen, Xilin2
刊名PATTERN RECOGNITION LETTERS
出版日期2024-03-01
卷号179页码:151-157
关键词Point cloud segmentation Synthetic data Domain adaptation
ISSN号0167-8655
DOI10.1016/j.patrec.2024.02.001
英文摘要The 3D comprehension ability of indoor environments is critical for robots. While deep learning-based methods have improved performance, they require significant amounts of annotated training data. Nevertheless, the cost of scanning and annotating point cloud data in real scenes is high, leading to data scarcity. Consequently, there is an urgent need to investigate data-efficient methods for point cloud instance segmentation. To tackle this issue, we propose to leverage the geometric and scene context knowledge inherent in synthetic data to reduce the need for annotation on real data. Specifically, we simulate the process of human scanning and collecting point cloud data in real -world scenes and construct three large-scale synthetic point cloud datasets using synthetic scenes. The scale of these three datasets is more than ten times that of currently available real -world data. Experimental results demonstrate that the incorporation of synthetic point cloud data can increase instance segmentation performance by over 18.8 percentage points. Further, to address the problem of domain shift between synthetic and real data, we propose a target-aware pre -training method. It integrates both real and synthetic data during the pre -training process, allowing the model to learn a feature representation that can effectively generalize to downstream real data. Experiments show that our method achieved stable improvements on all three synthetic datasets. The data and code will be publicly available in the future.
资助项目National Key R&D Program of China[2021ZD0111901] ; Natural Science Foundation of China[U21B2025] ; Natural Science Foundation of China[U19B2036]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:001197118000001
出版者ELSEVIER
源URL[http://119.78.100.204/handle/2XEOYT63/38766]  
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.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc Chinese Acad Sci, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Wu, Xiaodong,Wang, Ruiping,Chen, Xilin. Data-efficient 3D instance segmentation by transferring knowledge from synthetic scans[J]. PATTERN RECOGNITION LETTERS,2024,179:151-157.
APA Wu, Xiaodong,Wang, Ruiping,&Chen, Xilin.(2024).Data-efficient 3D instance segmentation by transferring knowledge from synthetic scans.PATTERN RECOGNITION LETTERS,179,151-157.
MLA Wu, Xiaodong,et al."Data-efficient 3D instance segmentation by transferring knowledge from synthetic scans".PATTERN RECOGNITION LETTERS 179(2024):151-157.

入库方式： OAI收割

来源：计算技术研究所

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