Explicit formulae for polyhedra moments
Pattern Recognition Letters
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Machine Learning
Dense sampling and fast encoding for 3D model retrieval using bag-of-visual features
Proceedings of the ACM International Conference on Image and Video Retrieval
International Journal of Computer Vision
Multimodal search and retrieval using manifold learning and query formulation
Proceedings of the 16th International Conference on 3D Web Technology
Optimizing multimedia retrieval using multimodal fusion and relevance feedback techniques
MMM'12 Proceedings of the 18th international conference on Advances in Multimedia Modeling
Benchmarks, performance evaluation and contests for 3D shape retrieval
Proceedings of the 10th Performance Metrics for Intelligent Systems Workshop
Feature template based 3D model retrieval
EG 3DOR'11 Proceedings of the 4th Eurographics conference on 3D Object Retrieval
SHREC'12 track: generic 3D shape retrieval
EG 3DOR'12 Proceedings of the 5th Eurographics conference on 3D Object Retrieval
CM-BOF: visual similarity-based 3D shape retrieval using Clock Matching and Bag-of-Features
Machine Vision and Applications
On 3D object retrieval benchmarking
3D Research
Dynamic maps for exploring and browsing shapes
SGP '13 Proceedings of the Eleventh Eurographics/ACMSIGGRAPH Symposium on Geometry Processing
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In this paper we present the results of the 3D Shape Retrieval Contest 2010 (SHREC'10) track Generic 3D Warehouse. The aim of this track was to evaluate the performances of various 3D shape retrieval algorithms on a large Generic benchmark based on the Google 3D Warehouse. We hope that the benchmark developed at NIST will provide valuable contributions to the 3D shape retrieval community. Three groups have participated in the track and they have submitted 7 set of results based on different methods and parameters. We also ran two standard algorithms on the track dataset. The performance evaluation of this track is based on six different metrics.