Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 2
616-622

RGB-D feature extraction network based on lightweight improved XYZNet

Yu Jianjun
Liu Gengyuan
Yu Naigong
Gong Daoxiong
Feng Xinyue
Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
DOI: 10.19734/j.issn.1001-3695.2023.06.0322

Abstract

According to the problem of the current RGB-D feature extraction network used for pose estimation is too large, this paper proposed a lightweight improved XYZNet RGB-D feature extraction network. Firstly, this paper designed a lightweight sub-network BaseNet to replace ResNet18 in XYZNet, which made the network scale significantly reduced and obtained more powerful performance. Then, this paper proposed a re-parameterized multi-scale convolutional attention(Rep-MSCA) sub-module based on depth separable convolution, which enhanced the ability of BaseNet to extract contextual information of different scales, and constrained the amount of parameters in the model. Finally, in order to improve the geometric feature extraction ability of PointNet in XYZNet with a small parameter cost, this paper designed a re-parameterized residual multi-layer perceptron(Rep-ResP) module. The floating point operations(FLOPs) and parameters of the improved network are 60.8% and 64.8% lower, the inference speed is 21.2% higher, and the accuracy of the mainstream datasets LineMOD and YCB-Video is 0.5% and 0.6% higher. The proposed model is more suitable for deployment in scenarios where hardware resources are tight.

Foundation Support

国家自然科学基金资助项目(62076014)
北京市教育委员会科技计划重点资助项目(KZ202010005004)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.06.0322
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 2
Section: Technology of Graphic & Image
Pages: 616-622
Serial Number: 1001-3695(2024)02-045-0616-07

Publish History

[2023-09-20] Accepted Paper
[2024-02-05] Printed Article

Cite This Article

于建均, 刘耕源, 于乃功, 等. 轻量化改进XYZNet的RGB-D特征提取网络 [J]. 计算机应用研究, 2024, 41 (2): 616-622. (Yu Jianjun, Liu Gengyuan, Yu Naigong, et al. RGB-D feature extraction network based on lightweight improved XYZNet [J]. Application Research of Computers, 2024, 41 (2): 616-622. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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