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Cited by 2,566Visual Attention and Saliency DetectionAdvanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

The DOI matches its Crossref record; 203 of the 213 references it cites were found in a registry or an index.

Attention mechanisms in computer vision: A survey

Open access
Guo, Meng-Hao, Xu, Tian-Xing, Liu, Jiang-Jiang, Liu, Zheng-Ning, Jiang, Peng-Tao, Mu, Tai-Jiang, Zhang, Song-Hai, Martin, Ralph R., Cheng, Ming-Ming, Hu, Shi-Min·2022·Computational Visual Media
DOI 10.1007/s41095-022-0271-y
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Abstract

Humans can naturally and effectively find salient regions in complex scenes. Motivated by this observation, attention mechanisms were introduced into computer vision with the aim of imitating this aspect of the human visual system. Such an attention mechanism can be regarded as a dynamic weight adjustment process based on features of the input image. Attention mechanisms have achieved great success in many visual tasks, including image classification, object detection, semantic segmentation, video understanding, image generation, 3D vision, multimodal tasks, and self-supervised learning. In this survey, we provide a comprehensive review of various attention mechanisms in computer vision and categorize them according to approach, such as channel attention, spatial attention, temporal attention, and branch attention; a related repository https://github.com/MenghaoGuo/Awesome-Vision-Attentions is dedicated to collecting related work. We also suggest future directions for attention mechanism research.

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Metadata

Authors
Guo, M.-H., Xu, T.-X., Liu, J.-J., Liu, Z.-N., Jiang, P.-T., Mu, T.-J., Zhang, S.-H., Martin, R. R., Cheng, M.-M., & Hu, S.-M.
Affiliations
  • Tsinghua University (CN)
  • TKLNDST, College of Computer Science, Nankai University, Tianjin 300350, China
  • Nankai University (CN)
  • Cardiff University (GB)
Corresponding author
Hu, Shi-Min
ORCID
Venue
Computational Visual Media
Publisher
Tsinghua University Press
Published
2022-09
Volume
8
Issue
3
Pages
331-368
ISSN
  • 2096-0433 (ISSN-L)
  • 2096-0662
DOI
10.1007/s41095-022-0271-y
OpenAlex
W3212386989
Cited by
2,566
References
213
Citations by year
2026: 404 · 2025: 687 · 2024: 739 · 2023: 576 · 2022: 159
FWCI
176.50
Type
journal article
Language
en
Open access
Licence
Locations
  • Computational Visual Media (publishedVersion, cc-by)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Funders
National Natural Science Foundation of China (62132012, 61521002)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
Keywords
attention mechanism, visual attention, channel attention, spatial attention, temporal attention, image classification, object detection, semantic segmentation, video understanding, image generation, 3D vision, multimodal tasks, self-supervised learning, human visual system

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