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Implementation for the paper: Uncertainty Estimation for 3D Dense Prediction via Cross-Point Embeddings

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(RA-L) Uncertainty Estimation for 3D Dense Prediction via Cross-Point Embeddings

CUE demo

We have named our proposed method CUE and demonstrated it in two tasks, 3D gemetric feature learning and 3D semantic segmentation. We organize the code in two directories to make it more readable:

If you find our work useful, please consider citing

@ARTICLE{10068211,
  author={Cai, Kaiwen and Lu, Chris Xiaoxuan and Huang, Xiaowei},
  journal={IEEE Robotics and Automation Letters}, 
  title={Uncertainty Estimation for 3D Dense Prediction via Cross-Point Embeddings}, 
  year={2023},
  volume={},
  number={},
  pages={1-8},
  doi={10.1109/LRA.2023.3256085}}

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Implementation for the paper: Uncertainty Estimation for 3D Dense Prediction via Cross-Point Embeddings

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  • Python 92.2%
  • Cuda 3.6%
  • C 2.8%
  • Shell 1.1%
  • Dockerfile 0.3%