To generate any data set, three steps are required: locate 3D models in the scene, set the discretization parameters, and finally run the generator. The set of rendered images provide data that can be used for geometric pattern recognition problems, such as depth estimation, camera pose estimation, 3D box estimation, 3D reconstruction, camera calibration, and also a pixel-perfect ground-truth for scene understanding problems (e.g., semantic segmentation, instance segmentation, object detection, just to cite a few).