Improved Deep Point Cloud Geometry Compression

@article{Quach2020ImprovedDP,
  title={Improved Deep Point Cloud Geometry Compression},
  author={Maurice Quach and G. Valenzise and F. Dufaux},
  journal={2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP)},
  year={2020},
  pages={1-6}
}
  • Maurice Quach, G. Valenzise, F. Dufaux
  • Published 2020
  • Computer Science, Engineering, Mathematics
  • 2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP)
Point clouds have been recognized as a crucial data structure for 3D content and are essential in a number of applications such as virtual and mixed reality, autonomous driving, cultural heritage, etc. In this paper, we propose a set of contributions to improve deep point cloud compression, i.e.: using a scale hyperprior model for entropy coding; employing deeper transforms; a different balancing weight in the focal loss; optimal thresholding for decoding; and sequential model training. In… Expand
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