Despite numerous recent efforts, 3D object retrieval based on partial shape queries remains a challenging problem, far from being solved. The problem can be defined as: given a partial view of a shape as query, retrieve all partially similar 3D models from a repository. The objective of this track is to evaluate the performance of partial 3D object retrieval methods, for partial shape queries of various qualities and degrees of partiality.

Important Dates

  • January 13

    Call for participation
  • February 19

    February 8

    Registration deadline
  • February 22

    February 12

    Distribution of the 3D partial query set
  • March 05

    February 22

    Submission of the results and one-page method description
  • March 15

    Track paper submission for review
  • April 1

    Camera-ready track paper submission
  • May 7-8

    SHREC 2016 in conjuction with 3DOR 2016


The dataset used for evaluation is related to the cultural heritage domain and consists of 3D pottery models originating from the Virtual Hampson Museum collection (http://hampson.cast.uark.edu). The dataset consists of 383 models classified to 6 distinct geometrically defined classes (bottle, bowl, jar, effigy, lithics and others).

The partial shape queries are provided in 3 different forms: (i) artificial queries created by slicing and cap filling of the complete 3D models, (ii) real high quality queries, obtained with the smartSCAN Breuckmann scanner, (iii) real low quality queries, obtained with Microsoft Kinect V2 sensor.

In the case of (ii) and (iii), the queries were created by scanning derivative vessels that have been constructed by a professional potter using the Hampson models as a template. For all 3 forms, queries are provided for multiple degrees of partiality.

Sample partial 3D queries and targets

Full partial queries and targets


Prospective participants are expected to:

  • Send an e-mail to ipratika(at)ee.duth.gr until the registration deadline (Feb 08, 2016), in order to confirm their participation. All group members and their affiliations should be indicated.
  • Submit a distance matrix for each retrieval setting. Each such setting is associated with one of the 3 different forms of queries, with a specified degree of partiality. Each matrix might be the result of a different algorithm, or a different parameter setting. It is not mandatory for each group to address all 3 forms of queries. Detailed information on the distance matrix file format will be provided soon.
  • Submit one or many runs.
  • Provide a one-page description of the testing method.

Each method will be evaluated based on its distance matrices, using standard retrieval scores (nearest neighbor, first tier, second tier, etc). The track results will be presented into a joint paper, to be published in the proceedings of EG 3DOR 2016

Register for Participation

All group members and their affiliations should be indicated


Ioannis Pratikakis

Democritus University of Thrace, Greece
Athena RC, Greece

Michalis Savelonas

Democritus University of Thrace, Greece
Athena RC, Greece

Fotis Arnaoutoglou

Democritus University of Thrace, Greece
Athena RC, Greece

Anestis Koutsoudis

Athena RC, Greece

Theoharis Theoharis

NTNU, Norway