Semantic Object Reconstruction

It is the official implementation of paper ''Semantic Object Reconstruction via Casual Handheld Scanning''.

Installation:

The code was developed by Microsoft Visual Studio 2015 on Windows 10.

Requirements:

• DirectX SDK June 2010
• Kinect SDK (prev. to 2.0)
• NVIDIA CUDA 8.0 (for the CUDA implementation)
• PCL-1.8.0

Optional:

• Kinect SDK (2.0 and above)
• Prime sense SDK

Input:

Our method takes RGB images, depth images, and part label images as input, and produces a reconstructed semantic object as output. In our paper, we conducted experiments using the Redwood dataset. This dataset contains only RGB-D scans; the labels can be obtained using any pre-trained neural network. All the images are organized as follows:

|--parent folder
      |--depth (*.png)
      |--rgb (*.jpg)
      |--label (*.png)

Some semantic reconstruction results:

Contact:

If you have any question, please feel free to contact me ([email protected]).

Citation

If you find our work useful in your research, please consider citing:

@article{hu2018semantic,
  title={Semantic object reconstruction via casual handheld scanning},
  author={Hu, Ruizhen and Wen, Cheng and Van Kaick, Oliver and Chen, Luanmin and Lin, Di and Cohen-Or, Daniel and Huang, Hui},
  journal={ACM Transactions on Graphics (TOG)},
  volume={37},
  number={6},
  pages={1--12},
  year={2018},
  publisher={ACM New York, NY, USA}
}

License

The code is released under MIT License (see LICENSE file for details).