SHREC 2021: Retrieval of Cultural Heritage Objects

  • 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.

Export metadata

Additional Services

Share in Twitter Search Google Scholar
Metadaten
Author:Ivan Sipiran, Patrick Lazo, Cristian Lopez, Nihar Bagewadi, Benjamin Bustos, Hieu Dao, Shankar Gangisetty, Martin Hanik, Ngoc-Phuong Ho-Thi, Mike Holenderski, Dmitri Jarnikov, Arniel Labrada, Stefan Lengauer, Roxane Licandro, Dinh-Huan Nguyen, Thang-Long Nguyen-Ho, Luis A. Pérez Rey, Bang-Dang Pham, Minh-Khoi Pham, Reinhold Preiner, Tobias Schreck, Quoc-Huy Trinh, Loek Tonnaer, Christoph von TycowiczORCiD, The-Anh Vu-Le
Document Type:Article
Parent Title (English):Computers and Graphics
Volume:100
First Page:1
Last Page:20
Fulltext Url:https://doi.org/10.1016/j.cag.2021.07.010
Year of first publication:2021
DOI:https://doi.org/10.1016/j.cag.2021.07.010