The present disclosure provides a neural network-based visual detection and tracking method of an inspection robot, which includes the following steps of: 1) acquiring environmental images of a dynamic background a movement process of the robot; 2) preprocessing the acquired images; 3) detecting human targets and specific behaviors in the images in the robot body, and saving the sizes, position information and features of the human targets with the specific behaviors; 4) controlling the orientation of a robot gimbal by using a target tracking algorithm to make sure that a specific target is always located at the central positions of the images; and 5) controlling the robot to move along with a tracked object. The neural network-based visual detection and tracking method of an inspection robot in the present disclosure has a quite high adaptive ability, achieves better detection and tracking effects on targets in a dynamic background scene.