Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds

PAConv

PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds

by Mutian Xu*, Runyu Ding*, Hengshuang Zhao, and Xiaojuan Qi.

Introduction

This repository is built for the official implementation of:

PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds (CVPR2021) [arXiv]

If you find our work useful in your research, please consider citing:

@inproceedings{xu2021paconv,
  title={PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds},
  author={Xu, Mutian and Ding, Runyu and Zhao, Hengshuang and Qi, Xiaojuan},
  booktitle={CVPR},
  year={2021}
}

Highlight

• All initialization models and trained models are available.
• Provide fast multiprocessing training (nn.parallel.DistributedDataParallel) with official nn.SyncBatchNorm.
• Incorporated with tensorboardX for better visualization of the whole training process.
• Support recent versions of PyTorch.
• Well designed code

   

   

   

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