Technology of Graphic & Image
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3180-3185

Driving scene segmentation enhancement algorithm based on multidimensional attention fusion

Liu Yichen1
Zhang Jianwu1
Hu Jing2
1. School of Communication Engineering, Hangzhou Dianzi University, Hangzhou 310018, China
2. Zhejiang Uniview Technologies Co. , Ltd. , Hangzhou 310051, China

Abstract

To address the problem of unbalanced computational resource consumption and accuracy of semantic segmentation models using attention mechanism, this paper proposed a lightweight attention enhancement algorithm for semantic segmentation. Firstly, it designed a striped dimensional attention mechanism based on the shape characteristics of objects in driving scenes, used striped pooling instead of traditional square convolution, and combined dimensionality reduction operations to extract long-range semantic associations in each dimension to cut down the model computation. Then it fused the attention on channel domain and spatial domain to form a lightweight multidimensional attention fusion module that could be superimposed and disassembled to extract feature information in all directions and further improve the model accuracy. Finally, it inserted the module into the ResNet-101 backbone based encoding-decoding network to guide the semantic fusion of high and low layers, correct the feature map edge information, and supplement the prediction details. The experiments show that the module has strong robustness and generalization ability, cutting about 90% of the number of parameters and 80% of the computation compared with the same type of attention mechanism, and the segmentation accuracy still achieves a stable improvement.

Foundation Support

国家自然科学基金资助项目(U1866209,61772162)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.01.0014
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 10
Section: Technology of Graphic & Image
Pages: 3180-3185
Serial Number: 1001-3695(2023)10-046-3180-06

Publish History

[2023-03-16] Accepted Paper
[2023-10-05] Printed Article

Cite This Article

刘奕晨, 章坚武, 胡晶. 基于多维注意力融合的驾驶场景分割增强算法 [J]. 计算机应用研究, 2023, 40 (10): 3180-3185. (Liu Yichen, Zhang Jianwu, Hu Jing. Driving scene segmentation enhancement algorithm based on multidimensional attention fusion [J]. Application Research of Computers, 2023, 40 (10): 3180-3185. )

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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