Deep learning has achieved remarkable results in target detection and classification when applied to computer vision. But in the field of object tracking, the target is only considered as a positive sample. Being lack of data support and more dependent on the location information, deep learning did not achieve remarkable effect in the object tracking field, while the traditional methods still occupy the main position. However, with the development of technology, deep learning has progressed greatly in the direction of object tracking in recent years. This paper introduces the basic concept and the main methods of target tracking technology. Combined with the development of deep learning in recent years in the field of target tracking, the emphasis is on the basic approach of target tracking technology with tracking by deep feature and tracking based on deep network and introduces the recently popular target tracking based on Siamese network in detail. At the end, the achievements of deep learning in the field of target tracking in recent years and future development of object tracking are summarized and prospected.