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 repositoryhttps://github.com/MenghaoGuo/Awesome-Vision-Attentionsis dedicated to collecting related work. We also suggest future directions for attention mechanism research.

Meng-Hao Guo

Tian-Xing Xu

Jiang-Jiang Liu

Zheng-Ning Liu

Peng-Tao Jiang

Tai-Jiang Mu

Song-Hai Zhang

Ralph R. Martin

Ming-Ming Cheng

Shi-Min Hu

Computational Visual Media

Comp. Visual Media

Attention mechanisms in computer vision: A survey

计算机视觉中的注意力机制：综述

Category	Quartile
计算机科学	3
计算机科学, 计算机软件工程	3

Attention mechanisms in computer vision: A survey

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Journal Info

Category	Quartile
COMPUTER SCIENCE, SOFTWARE ENGINEERING	1