AlignNet-3D: Fast Point Cloud Registration of Partially Observed Objects

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Paper

AlignNet-3D for Fast Point Cloud Registration of Partially Observed Objects

Code + Data

github

Copyright for the Synthetic Data

Creative Commons License

Data on this page are published under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. This means that you must attribute the work in the manner specified by the authors, you may not use this work for commercial purposes and if you alter, transform, or build upon this work, you may distribute the resulting work only under the same license.

Citation

If you use our code/data, please cite:

@INPROCEEDINGS{Gross193DV,
  author = {Johannes Gro\ss and Aljo\v{s}a O\v{s}ep and Bastian Leibe},
  title = {AlignNet-3D: Fast Point Cloud Registration of Partially Observed Objects},
  booktitle = {International Conference on 3D Vision (3DV)},
  year = {2019}

}

and also the original datasets:

@INPROCEEDINGS{Geiger2012CVPR,
  author = {Andreas Geiger and Philip Lenz and Raquel Urtasun},
  title = {Are we ready for Autonomous Driving? The KITTI Vision Benchmark Suite},
  booktitle = {Conference on Computer Vision and Pattern   Recognition (CVPR)},
  year = {2012}

}

Contact

If you have questions, please contact Johannes Groß via johannes.gross1@rwth-aachen.de or Aljosa Osep via osep@vision.rwth-aachen.de