The traditional target detection algorithm and strategy has been difficult to meet the target detection of data processing efficiency,performance,speed and intelligence and other aspects.Depth learning through the study of brain cognitive ability and imitation to achieve the analysis of data characteristics of the treatment,with a strong visual target detectioncapabilities,has become the current target detection of the mainstream algorithm.Firstly,the developmentand problems of traditional target detectionare reviewed;Secondly,the target detection framework which combines region proposal and CNNclassification with RCNN is introduced(RCNN,SPPNET,Fast RCNN, Faster RCNN);Then,the target detection framework is introduced,which is based on YOLO(YOLO,SSD)algorithm;Finally,this paper makes a summary of the problemsexisting in the target detection algorithm of deep learning and the development of the future.