SHREC'16 track large-scale 3D shape retrieval from ShapeNet Core55

M. Savva, F. Yu, Hao Su, M. Aono, B. Chen, D. Cohen-Or, W. Deng, Hang Su, S. Bai, X. Bai, N. Fish, J. Han, E. Kalogerakis, E. G. Learned-Miller, Y. Li, M. Liao, S. Maji, A. Tatsuma, Y. Wang, N. ZhangZ. Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


With the advent of commodity 3D capturing devices and better 3D modeling tools, 3D shape content is becoming increasingly prevalent. Therefore, the need for shape retrieval algorithms to handle large-scale shape repositories is more and more important. This track aims to provide a benchmark to evaluate large-scale shape retrieval based on the ShapeNet dataset. We use ShapeNet Core55, which provides more than 50 thousands models over 55 common categories in total for training and evaluating several algorithms. Five participating teams have submitted a variety of retrieval methods which were evaluated on several standard information retrieval performance metrics. We find the submitted methods work reasonably well on the track benchmark, but we also see significant space for improvement by future algorithms. We release all the data, results, and evaluation code for the benefit of the community.

Original languageEnglish
Title of host publicationEG 3DOR 2016 - Eurographics 2016 Workshop on 3D Object Retrieval
EditorsAlfredo Ferreira, Daniela Giorgi, Andrea Giachetti
PublisherEurographics Association
Number of pages10
ISBN (Electronic)9783038680048
StatePublished - 2016
Event9th Eurographics Workshop on 3D Object Retrieval, 3DOR 2016 - Lisbon, Portugal
Duration: 8 May 2016 → …

Publication series

NameEurographics Workshop on 3D Object Retrieval, EG 3DOR
ISSN (Print)1997-0463
ISSN (Electronic)1997-0471


Conference9th Eurographics Workshop on 3D Object Retrieval, 3DOR 2016
Period8/05/16 → …


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