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ShapeNet: An Information-Rich 3D Model Repository

About

We present ShapeNet: a richly-annotated, large-scale repository of shapes represented by 3D CAD models of objects. ShapeNet contains 3D models from a multitude of semantic categories and organizes them under the WordNet taxonomy. It is a collection of datasets providing many semantic annotations for each 3D model such as consistent rigid alignments, parts and bilateral symmetry planes, physical sizes, keywords, as well as other planned annotations. Annotations are made available through a public web-based interface to enable data visualization of object attributes, promote data-driven geometric analysis, and provide a large-scale quantitative benchmark for research in computer graphics and vision. At the time of this technical report, ShapeNet has indexed more than 3,000,000 models, 220,000 models out of which are classified into 3,135 categories (WordNet synsets). In this report we describe the ShapeNet effort as a whole, provide details for all currently available datasets, and summarize future plans.

Angel X. Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, Fisher Yu• 2015

Related benchmarks

TaskDatasetResultRank
3D Object ClassificationModelNet40--
62
3D Shape RetrievalModelNet40 (test)
mAP49.2
38
Object ClassificationScanObjectNN
Accuracy74.5
29
3D Object DetectionKITTI (val)
AP3D R40 Easy19.64
24
3D Object ClassificationScanNet 10
Accuracy0.723
17
3D Shape GenerationShapeNet Airplane (test)
FPD0.009
5
3D Shape GenerationShapeNet Car (test)
FPD0.128
5
3D Shape GenerationShapeNet Chair (test)
FPD0.086
5
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