Sipiran, IvanRomanengo, ChiaraFalcidieno, BiancaBiasotti, SilviaArvanitis, GerasimosChen, ChenFotis, VlassisHe, JianfangLv, XiaolingMoustakas, KonstantinosPeng, SilongRomanelis, IoannisSun, WenhaoVlachos, ChristoforosWu, ZiyuXie, QiongFugacci, UldericoLavoué, GuillaumeVeltkamp, Remco C.2023-08-302023-08-302023978-3-03868-213-41997-0471https://doi.org/10.2312/3dor.20231148https://diglib.eg.org:443/handle/10.2312/3dor20231148This paper presents the methods that participated in the SHREC 2023 track focused on detecting symmetries on 3D point clouds representing simple shapes. By simple shapes, we mean surfaces generated by different types of closed plane curves used as the directrix of a cylinder or a cone. This track aims to determine the reflective planes for each point cloud. The methods are evaluated in their capability of detecting the right number of symmetries and correctly identifying the reflective planes. To this end, we generated a dataset that contains point clouds representing simple shapes perturbed with different kinds of artefacts (such as noise and undersampling) to provide a thorough evaluation of the robustness of the algorithms.Attribution 4.0 International LicenseCCS Concepts: Computing methodologies → Shape analysis; Point-based modelsComputing methodologies → Shape analysisPoint based models10.2312/3dor.202311481-88 pages