Completion3D: Stanford 3D Point Cloud Completion Benchmark


The Completion3D benchmark is a platform for evaluating state-of-the-art 3D Object Point Cloud Completion methods. Participants are given a partial 3D object point cloud and tasked to infer a complete 3D point cloud for the object.



Input


AtlasNet


Folding


PCN


TopNet


Ground-truth




Participate


To participate in the Completion3D benchmark:

  • Download the 2048K points   dataset
  • EVALUATION COMING SOON!!  Download the 16384K points  dataset
  • Create an account
  • Submit your results as a zip file with the same folder structure as the input dataset

Starter code with various baselines can be found in the TopNet and Completion3D github repository


Publications


If you use the Completion3D benchmark in your work, please cite the following publications:

TopNet: Structural Point Cloud Decoder
Lyne P. Tchapmi, Vineet Kosaraju, Hamid Rezatofighi, Ian Reid and Silvio Savarese
CVPR 2019

PCN: Point Completion Network
Wentao Yuan, Tejas Khot, David Held, Christoph Mertz and Martial Hebert
3DV 2018(Oral)

ShapeNet: An Information-Rich 3D Model Repository
Angel X. Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi and Fisher Yu
Arxiv 2015
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