Large-Scale 3D Shape Retrieval from ShapeNet Core55 (Unknown language)

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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.

Table of contents conference proceedings

The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.

1
Shape Retrieval and 3D Gestural Interaction
Giachetti, Andrea / Caputo, Fabio Marco / Carcangiu, Alessandro / Scateni, Riccardo / Spano, Lucio Davide | 2016
5
Towards an Observer-oriented Theory of Shape Comparison
Frosini, Patrizio | 2016
9
3D Objects Exploration: Guidelines for Future Research
Biasotti, Silvia / Falcidieno, Bianca / Giorgi, Daniela / Spagnuolo, Michela | 2016
13
A Descriptor for Voxel Shapes Based on the Skeleton Cut Space
Feng, Cong / Jalba, Andrei C. / Telea, Alexandru C. | 2016
21
An Experimental Shape Matching Approach for Protein Docking
Fernandes, Francisco / Ferreira, Alfredo | 2016
27
An Edit Distance for Reeb Graphs
Bauer, Ulrich / Fabio, Barbara Di / Landi, Claudia | 2016
35
An Evaluation of Local Feature Encodings for Shape Retrieval
Tasse, Flora Ponjou / Kosinka, Jiri / Dodgson, Neil A. | 2016
41
Retrieval of Human Subjects from Depth Sensor Data
Giachetti, Andrea / Fornasa, Francesco / Parezzan, Federico / Saletti, Alessandro / Zambaldo, Leonardo / Zanini, Luisa / Achilles, Felix / Ichim, Alexandru-Eugen / Tombari, Federico / Navab, Nassir et al. | 2016
47
3D Sketch-Based 3D Shape Retrieval
Li, Bo / Lu, Yijuan / Duan, Fuqing / Dong, Shuilong / Fan, Yachun / Qian, Lu / Laga, Hamid / Li, Haisheng / Li, Yuxiang / Liu, Peng et al. | 2016
55
Matching of Deformable Shapes with Topological Noise
Lähner, Zorah / Rodolà, Emanuele / Bronstein, Michael M. / Cremers, Daniel / Burghard, Oliver / Cosmo, Luca / Dieckmann, Alexander / Klein, Reinhard / Sahillioğlu, Yusuf | 2016
61
Partial Matching of Deformable Shapes
Cosmo, Luca / Rodolà, Emanuele / Bronstein, Michael M. / Torsello, Andrea / Cremers, Daniel / Sahillioğlu, Yusuf | 2016
69
Shape Retrieval of Low-Cost RGB-D Captures
Pascoal, Pedro B. / Proença, Pedro / Gaspar, Filipe / Dias, Miguel Sales / Ferreira, Alfredo / Tatsuma, Atsushi / Aono, Masaki / Logoglu, K. Berker / Kalkan, Sinan / Temizel, Alptekin et al. | 2016
79
Partial Shape Queries for 3D Object Retrieval
Pratikakis, Ioannis / Savelonas, Michalis A. / Arnaoutoglou, Fotis / Ioannakis, George / Koutsoudis, Anestis / Theoharis, Theoharis / Tran, Minh-Triet / Nguyen, Vinh-Tiep / Pham, V.-K. / Nguyen, Hai-Dang et al. | 2016
89
Large-Scale 3D Shape Retrieval from ShapeNet Core55
Savva, Manolis / Yu, Fisher / Su, Hao / Aono, Masaki / Chen, Baoquan / Cohen-Or, Daniel / Deng, Weihong / Su, Hang / Bai, Song / Bai, Xiang et al. | 2016
99
3D Object Retrieval with Multimodal Views
Gao, Yue / Nie, Weizhi / Liu, Anan / Su, Yuting / Dai, Qionghai / An, Le / Chen, Fuhai / Cao, Liujuan / Dong, Shuilong / De, Yu et al. | 2016