Example-based color transfer between images, which has raised a lot of interest in the past decades, consists of transferring the color of an image to another one. Many methods based on color distributions have been proposed, and more recently, the efficiency of neural networks has been demonstrated again for color transfer problems. In this paper, we propose a new pipeline with methods adapted from the image domain to automatically transfer the color from a target point cloud to an input point cloud. These color transfer methods are based on color distributions and account for the geometry of the point clouds to produce a coherent result. The proposed methods rely on simple statistical analysis, are effective, and succeed in transferring the color style from one point cloud to another. The qualitative results of the color transfers are evaluated and compared with existing methods.