In recent years,fine-grained image recognition has become a hotspot in computer vision area.Due to the subtle visual differences among different image categories and the serious semantic gap,the performance of traditional image recognition algorithms for fine-grained images recognition is mostly unsatisfactory.To overcome these challenges,many researchers have been concentrating on image recognition with user click data.This paper focuses on the three key modules of the fine-grained recognition system with user click data:data pre-processing,feature extracting and model construction.Also,existing algorithms for click data based image recognition are summarized,and the related latest progresses are demonstrated.