The target detection based on deep learning technology extracts and learns multi-level features of the target through artificial neural network, and sends the feature map to the classifier to predict the category and position of the target.According to the model training methods, the algorithms can be divided into two types:one-stage detection algorithm and two-stage detection algorithm.In this paper, the representative algorithms of each stage are introduced in detail, and comparison and analysis are made to the algorithms on the PASCAL VOC data set.Finally, the development trend of target detection is forecasted.