A new method of target tracking for monocular vision underwater robot based on deep learning is introduced. This method could be adopted to realize autonomous underwater vehicle (AUV) image enhancement processing and target recognition tracking in underwater complex environment for each acquisition. Every video frame was calculated using a pre-processed deep convolutional neural network. A correlation estimate of the image depth information was provided by the image transmission map. The underwater target area could be identified by the method and the underwater target motion and tracking direction be indicated. The experiment shows that the method can obtain the positioning data in the underwater environment more accurately and stably.