SHREC'14 Track: Large Scale Comprehensive 3D Shape Retrieval

By Bo Li, Yijuan Lu, Chunyuan Li, A. Godil, Tobias Schreck, Masaki Aono, Qiang Chen, Bin Fang, Takahiko Furuya, H. Johan and 4 more. 2014

33 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

ShapeNet: An Information-Rich 3D Model Repository (2015, background): “annually for the Shape Retrieval Contest (SHREC) that commonly contains sets of models organized in object categories. However, those datasets are very small — the most recent SHREC iteration in 2014 [17] contains a “large” dataset with around 9,000 models consisting of models from a variety of sour”
The YCB object and Model set: Towards common benchmarks for manipulation research (2015, background): “Even though there are a large number of efforts (e.g. [1, 2, 4, 12-15]) that provide mesh model datasets of objects, these datasets have limited utility for manipulation benchmarking due to several reasons: First, since most of them are not designed specifically for manipulation benchmarking, the…”
Benchmarking in Manipulation Research: The YCB Object and Model Set and Benchmarking Protocols (2015, background): “[1-4] with a thorough overview provided in section II), generally for object recognition or planning purposes.”
Benchmarking in Manipulation Research: Using the Yale-CMU-Berkeley Object and Model Set (2015, background): “Such work has often been created for research in computer vision (see [2], [16], and [17]).”