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.

@techreport{Chang:2015:SAI,
   author = "Angel X. Chang and Thomas Funkhouser and Leonidas Guibas and Pat
      Hanrahan and Qixing Huang and Zimo Li and Silvio Savarese and
      Manolis Savva and Shuran Song and Hao Su and Jianxiong Xiao and
      Li Yi and Fisher Yu",
   title = "{ShapeNet}: An Information-Rich {3D} Model Repository",
   institution = "arXiv preprint",
   year = "2015",
   month = dec,
   number = "1512.03012"
}