TY - JOUR A1 - Sipiran, Ivan A1 - Lazo, Patrick A1 - Lopez, Cristian A1 - Bagewadi, Nihar A1 - Bustos, Benjamin A1 - Dao, Hieu A1 - Gangisetty, Shankar A1 - Hanik, Martin A1 - Ho-Thi, Ngoc-Phuong A1 - Holenderski, Mike A1 - Jarnikov, Dmitri A1 - Labrada, Arniel A1 - Lengauer, Stefan A1 - Licandro, Roxane A1 - Nguyen, Dinh-Huan A1 - Nguyen-Ho, Thang-Long A1 - Pérez Rey, Luis A. A1 - Pham, Bang-Dang A1 - Pham, Minh-Khoi A1 - Preiner, Reinhold A1 - Schreck, Tobias A1 - Trinh, Quoc-Huy A1 - Tonnaer, Loek A1 - von Tycowicz, Christoph A1 - Vu-Le, The-Anh T1 - SHREC 2021: Retrieval of Cultural Heritage Objects JF - Computers and Graphics N2 - This paper presents the methods and results of the SHREC’21 contest on a dataset of cultural heritage (CH) objects. We present a dataset of 938 scanned models that have varied geometry and artistic styles. For the competition, we propose two challenges: the retrieval-by-shape challenge and the retrieval-by-culture challenge. The former aims at evaluating the ability of retrieval methods to discriminate cultural heritage objects by overall shape. The latter focuses on assessing the effectiveness of retrieving objects from the same culture. Both challenges constitute a suitable scenario to evaluate modern shape retrieval methods in a CH domain. Ten groups participated in the contest: thirty runs were submitted for the retrieval-by-shape task, and twenty-six runs were submitted for the retrieval-by-culture challenge. The results show a predominance of learning methods on image-based multi-view representations to characterize 3D objects. Nevertheless, the problem presented in our challenges is far from being solved. We also identify the potential paths for further improvements and give insights into the future directions of research. Y1 - 2021 U6 - https://doi.org/10.1016/j.cag.2021.07.010 VL - 100 SP - 1 EP - 20 ER -