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PointGrid: A Deep Network for 3D Shape Understanding

Prerequisites:

  1. Python (with necessary common libraries such as numpy, scipy, etc.)
  2. TensorFlow
  3. You need to prepare your data in *.mat file with the following format:
    • 'points': N x 3 array (x, y, z coordinates of the point cloud)
    • 'labels': N x 1 array (1-based integer per-point labels)
    • 'category': scalar (0-based integer model category)

Train:

python train.py

Test:

python test.py

If you find this code useful, please cite our work at

@article{PointGrid,
	author = {Truc Le and Ye Duan},
	titile = {{PointGrid: A Deep Network for 3D Shape Understanding}},
	journal = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
	month = {June},
	year = {2018},
}

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