GRNet: Gridding Residual Network for Dense Point Cloud Completion

@article{Xie2020GRNetGR,
  title={GRNet: Gridding Residual Network for Dense Point Cloud Completion},
  author={Haozhe Xie and Hongxun Yao and Shangchen Zhou and Jiageng Mao and Shengping Zhang and Wenxiu Sun},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.03761}
}
Estimating the complete 3D point cloud from an incomplete one is a key problem in many vision and robotics applications. Mainstream methods (e.g., PCN and TopNet) use Multi-layer Perceptrons (MLPs) to directly process point clouds, which may cause the loss of details because the structural and context of point clouds are not fully considered. To solve this problem, we introduce 3D grids as intermediate representations to regularize unordered point clouds. We therefore propose a novel Gridding… 

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