The LiDAR sensor, which detects the relative distance to an object, is widely used in the field of 3D object detection based on point cloud, and is a key sensor in autonomous vehicles because it can recognize the distance and shape of the surrounding object. The LiDAR sensor extracts different features even when looking at the same object depending on the installation location and angle. Usually, the open dataset and the user's LiDAR installation location are different. In this case, the performance of the model trained with the open dataset is not fully exhibited. We propose a method and model to convert the point cloud data acquired from the source location to the point cloud acquired from the target location.