The project proposed is finalized to develop a novel network for Point Cloud denoising based on Graphs. A Point Cloud is an object representation composed by a collection of 3-D space coordinates. This data is usually acquired by radar, laser, Electro-Optical systems or by reconstruction of 2-D images: all these methods lead to point cloud typically affected by noise. The aim of the project is to design a network able to efficiently produce cleaned 3-D point cloud from a noisy observation. Denoising task is a typical problem addressed in Image Processing and the current state-of-the-art is Convolutional Neural Network (CNN), that leads to promising results for noise removal in images; the idea developed in this project is to exploit a Deep Neural Network, composed by convolutional layers, introducing appropriate adjustment for the Point Cloud denoising task.