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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 9

Expression recognition network of channel-spatial multi-scale enhancement and dual-pooling attention

Liu Juan1
Zhang Minyang1
Hu Min2
Huang Zhong1,2
Jiang Julang1
1. School of Electronic Engineering & Intelligent Manufacturing, Anqing Normal University, Anqing Anhui 246133, China
2. Anhui Province Key Laboratory of Affective Computing & Advanced Intelligent Machine, School of Computer & Information, Hefei University of Technology, Hefei Anhui 230009, China
DOI: 10.19734/j.issn.1001-3695.2024.12.0524

Abstract

Aiming at the problems that expression feature extraction in natural scenes only focuses on channel-spatial single-scale information and average pooling is easy to lose local saliency semantics, this paper proposes an expression recognition network of channel-spatial multi-scale enhancement and dual-pooling attention. Firstly, to capture the whole channel-spatial multi-scale enhancement semantics, this paper designs a channel symmetric cascade multi-scale module and a spatial multi-scale feature extraction module, and constructs a whole feature enhancement subnetwork based on the channel-spatial multi-scale structure. Then, to represent the channel-spatial region dual-pooling salient semantics, this paper improves the efficient local attention mechanism into an efficient channel-spatial attention mechanism, and embeds it into the region feature attention subnetwork. Finally, to obtain the potential correlation between the whole multi-scale enhanced semantics and the regional dual-pooling salient semantics, this paper uses the cross-attention mechanism to perform the feature interaction between the whole features and the regional features, and designs the feature fusion subnetwork to complete the model-level fusion of the two types of features. The experimental results show that the expression recognition rates on the facial expression datasets RAF-DB and FERPlus reach 89.97% and 90.26% respectively, which are 13.54% and 10.95% higher than the baseline network. Compared with other networks, the proposed network has better expression recognition performance in natural scenes.

Foundation Support

国家自然科学基金资助项目(62176084)
安徽省教育厅自然科学重点研究项目(2022AH051038,2023AH050500,2023AH050474)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.12.0524
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 9

Publish History

[2025-04-29] Accepted Paper

Cite This Article

刘娟, 张民扬, 胡敏, 等. 通道-空间多尺度增强与双池化注意的表情识别网络 [J]. 计算机应用研究, 2025, 42 (9). (2025-04-29). https://doi.org/10.19734/j.issn.1001-3695.2024.12.0524. (Liu Juan, Zhang Minyang, Hu Min, et al. Expression recognition network of channel-spatial multi-scale enhancement and dual-pooling attention [J]. Application Research of Computers, 2025, 42 (9). (2025-04-29). https://doi.org/10.19734/j.issn.1001-3695.2024.12.0524. )

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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