The goal of this document is to survey existing methods for recovering CSG representations from unstructured data such as 3D point-clouds or polygon meshes. We review and discuss related topics such as the segmentation and fitting of the input data. We cover techniques from solid modeling and CAD for polyhedron to CSG and B-rep to CSG conversion. We look at approaches coming from program synthesis, evolutionary techniques (such as genetic programming or genetic algorithm), and deep learning methods. Finally, we conclude with a discussion of techniques for the generation of computer programs representing solids (not just CSG models) and higher-level representations (such as, for example, the ones based on sketch and extrusion or feature based operations).

翻译：本文旨在综述现有从非结构化数据（如三维点云或多边形网格）恢复CSG表示的方法。我们回顾并讨论了输入数据的分割与拟合等相关主题。涵盖了实体建模与CAD领域中多面体到CSG、B-rep到CSG转换的技术。我们探讨了来自程序合成、进化技术（如遗传编程或遗传算法）以及深度学习的方法。最后，我们讨论了表示实体的计算机程序生成技术（不仅限于CSG模型）及更高层次表示（例如基于草图与拉伸或特征操作的方法）。