Attention mechanisms in computer vision: A survey
Attention mechanisms in computer vision: A survey
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Beijing: Tsinghua University Press
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Language
English
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Publisher
Beijing: Tsinghua University Press
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Contents
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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Full title
Attention mechanisms in computer vision: A survey
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TN_cdi_proquest_journals_2652733969
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2652733969
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ISSN
2096-0433
E-ISSN
2096-0662
DOI
10.1007/s41095-022-0271-y
