Abstract: Traditional target detection algorithms rely mainly on manually selecting features to detect objects. The artificially extracted feature pairs are mainly for certain specific objects, such as some features suitable for edge detection, and some suitable for texture detection, which is not universal. In recent years, deep learning has flourished, and significant research progress has been made in the field of computer vision such as image classification, target detection, and image semantic segmentation. As a feature learning method, deep learning can automatically learn the useful features of the target, avoiding the problem of manual extraction of features, and at the same time ensuring good detection results. Firstly, the research progress of target detection algorithm based on deep learning is introduced. Secondly, the common problems and solutions in target detection algorithm are summarized. Finally, the possible development direction of target detection algorithm is prospected.

Key words: target detection, deep learning, computer vision