Summary of fine-grained image recognition based on attention mechanism

Attention mechanism is one of the most basic and core tasks in computer vision. Its essence is to locate the information in the region of interest and suppress useless information. The results are usually displayed in the form of probability graph or probability eigenvector. Attention mechanism has become an important concept in convolutional neural network, which has been widely studied in different application fields and has strong practical value. This paper introduces the classification of attention mechanism and its application in fine-grained image recognition. The classification is mainly divided into channel attention mechanism, spatial attention mechanism and channel spatial mixed attention mechanism. Finally, the future research direction of attention mechanism in fine-grained images is discussed.