Minimal Adversarial Examples for Deep Learning on 3D Point Clouds

@article{Kim2021MinimalAE,
  title={Minimal Adversarial Examples for Deep Learning on 3D Point Clouds},
  author={Jaeyeon Kim and Binh-Son Hua and Duc Thanh Nguyen and Sai-Kit Yeung},
  journal={2021 IEEE/CVF International Conference on Computer Vision (ICCV)},
  year={2021},
  pages={7777-7786}
}
With recent developments of convolutional neural net-works, deep learning for 3D point clouds has shown significant progress in various 3D scene understanding tasks, e.g., object recognition, semantic segmentation. In a safety-critical environment, it is however not well understood how such deep learning models are vulnerable to adversarial examples. In this work, we explore adversarial attacks for point cloud-based neural networks. We propose a unified formulation for adversarial point cloud… 

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