SUNCG is an ongoing effort to establish a richly-annotated, large-scale dataset of 3D scenes. The dataset contains over 45K different scenes with manually created realistic room and furniture layouts. All of the scenes are semantically annotated at the object level. This website provides
  • Some basic statistics of the dataset.
  • A C++ toolbox for loading and viewing the data.
  • An online scene query GUI for exploring the dataset.
  • If you are a researcher and would like to get access to the data, please print and sign this agreement and email it to Shuran Song: shurans [at] princeton [dot] edu.


  • Initial data and toolbox release. Jan 1st 2017
  • Bibtex

        title= {Semantic Scene Completion from a Single Depth Image},
        author= {Song, Shuran and Yu, Fisher and Zeng, Andy and Chang, Angel X and Savva, Manolis and Funkhouser, Thomas},
        journal={IEEE Conference on Computer Vision and Pattern Recognition},