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Deep 3D point cloud models are sensitive to adversarial attacks, which poses threats to safety-critical applications such as autonomous driving.
Towards 3D point cloud based object maps for household environments
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PointCloud saliency maps. In ICCV
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DUP-Net: Denoiser and upsampler network for 3D adversarial point clouds defense. In ICCV
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Walk in the cloud: Learning curves for point clouds shape analysis. In ICCV
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Shape-invariant 3D adversarial point clouds. In CVPR
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Boosting 3D adversarial attacks with attacking on frequency
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Convolutional occupancy networks. In European Conference on Computer Vision
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Robust adversarial objects against deep learning models. In AAAI
Tzungyu Tsai, Kaichen Yang, Tsung-Yi Ho, and Yier Jin. 2020 · 2020
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Ziyi Wu, Yueqi Duan, He Wang, Qingnan Fan, and Leonidas J Guibas. 2020 · 2020
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LG-GAN: Label guided adversarial network for flexible targeted attack of point cloud based deep networks. In CVPR
Hang Zhou, Dongdong Chen, Jing Liao, Kejiang Chen, Xiaoyi Dong, Kunlin Liu, Weiming Zhang, Gang Hua, and Nenghai Yu. 2020 · 2020
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PCT: Point cloud transformer
Meng-Hao Guo, Junxiong Cai, Zheng-Ning Liu, Tai-Jiang Mu, Ralph Robert Martin, and Shimin Hu. 2021 · 2021
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Minimal adversarial examples for deep learning on 3D point clouds. In ICCV
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Diffusion models for adversarial purification. In ICML
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PointDP: Diffusion-driven purification against adversarial attacks on 3D point cloud recognition
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Guided diffusion model for adversarial purification
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LION: Latent point diffusion models for 3D shape generation. In NeruIPS
Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, and Karsten Kreis. 2022 · 2022
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