The main purpose of object detection is to detect and locate specific targets from images. The traditional detection methods are usually complex and require prior knowledge of the detection target. In this paper, we will introduce how to use convolutional neural networks to perform object detection from image. This is one of the important areas of computer vision. In order to build up to object detection, we first learn about how we can get the object localization or landmark by a neural network. And then I will give the detail of sliding windows detection algorithm and introduce how to use the convolutional implementation of sliding windows to speed up the process. Then we will introduce the transfer learning and how to prepare your own learning data for training networks.