Skip to content

idrl-lab/A-Paperlist-of-Adversarial-Attack-on-3D-Object-Detection

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 

Repository files navigation

A Paper List of Adversarial Attack on 3D Object Detection

2021

  • Cao, Yulong, et al. "Invisible for both camera and lidar: Security of multi-sensor fusion based perception in autonomous driving under physical-world attacks." 2021 IEEE Symposium on Security and Privacy (SP). IEEE, 2021. pdf
  • Hau, Zhongyuan, et al. "Object removal attacks on lidar-based 3d object detectors." arXiv preprint arXiv:2102.03722 (2021). pdf
  • Li, Yiming, et al. "Fooling lidar perception via adversarial trajectory perturbation." arXiv preprint arXiv:2103.15326 (2021). pdf
  • Abdelfattah, Mazen, et al. "Adversarial Attacks on Camera-LiDAR Models for 3D Car Detection." arXiv preprint arXiv:2103.09448 (2021). pdf
  • Yang, Kaichen, et al. "Robust Roadside Physical Adversarial Attack Against Deep Learning in Lidar Perception Modules." Proceedings of the 2021 ACM Asia Conference on Computer and Communications Security. 2021. pdf
  • Abdelfattah, Mazen, et al. "Towards Universal Physical Attacks On Cascaded Camera-Lidar 3D Object Detection Models." arXiv preprint arXiv:2101.10747 (2021). pdf
  • Park, Won, et al. "Sensor Adversarial Traits: Analyzing Robustness of 3D Object Detection Sensor Fusion Models." 2021 IEEE International Conference on Image Processing (ICIP). IEEE, 2021. pdf
  • Liu, Bingyu, et al. "Multi-view Correlation based Black-box Adversarial Attack for 3D Object Detection." Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. 2021. pdf
  • Wang, Huiying, et al. "Generating Adversarial Point Clouds on Multi-modal Fusion Based 3D Object Detection Model." International Conference on Information and Communications Security. Springer, Cham, 2021. pdf

2020

  • Tu, James, et al. "Physically realizable adversarial examples for lidar object detection." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2020. pdf
  • Won Park, Q. Chen, Z. Mao, Crafting Adversarial Examples on 3D Object Detection Sensor Fusion Models, Proceedings of CVPR 2020 Workshop on Adversarial Machine Learning in Computer Vision 2020. pdf
  • Jiachen Sun, Yulong Cao, Q. Chen, Z. Mao, Towards Robust LiDAR-based Perception in Autonomous Driving, Proceedings of CVPR 2020 Workshop on Adversarial Machine Learning in Computer Vision 2020. pdf
  • Jiachen Sun, Yulong Cao, Qi Alfred Chen, and Z Morley Mao. 2020. Towards robust lidar-based perception in autonomous driving: General black-box adversarial sensor attack and countermeasures. In 29th {USENIX} Security Symposium ({USENIX} Security 20). 877–894. pdf
  • Yiren Zhao, Ilia Shumailov, Robert Mullins, and Ross Anderson. Nudge attacks on point-cloud dnns. arXiv preprint arXiv:2011.11637, 2020. pdf
  • Cai, Mumuxin, et al. "Adversarial point cloud perturbations to attack deep object detection models." 2020 IEEE 22nd International Conference on High Performance Computing and Communications; IEEE 18th International Conference on Smart City; IEEE 6th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). IEEE, 2020. pdf
  • Ren, Huali, and Teng Huang. "Adversarial Example Attacks in the Physical World." International Conference on Machine Learning for Cyber Security. Springer, Cham, 2020. pdf
  • Cao, Yulong, et al. "3D adversarial object against msf-based perception in autonomous driving." Proceedings of the 3rd Conference on Machine Learning and Systems. 2020. pdf

2019

  • Jiancheng Yang, Qiang Zhang, Rongyao Fang, Bingbing Ni, Jinxian Liu, and Qi Tian. Adversarial attack and defense on point sets. arXiv preprint arXiv:1902.10899, 2019. 2 pdf
  • Xiang, Chong, Charles R. Qi, and Bo Li. "Generating 3d adversarial point clouds." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2019. pdf
  • Zheng, Tianhang, et al. "Pointcloud saliency maps." Proceedings of the IEEE/CVF International Conference on Computer Vision. 2019. pdf
  • Wicker, Matthew, and Marta Kwiatkowska. "Robustness of 3d deep learning in an adversarial setting." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2019. pdf
  • Liu, Daniel, Ronald Yu, and Hao Su. "Adversarial point perturbations on 3d objects." arXiv e-prints (2019): arXiv-1908. pdf
  • Cao, Yulong, et al. "Adversarial objects against lidar-based autonomous driving systems." arXiv preprint arXiv:1907.05418 (2019). pdf
  • Yulong Cao, Chaowei Xiao, Benjamin Cyr, Yimeng Zhou, Won Park, Sara Rampazzi, Qi Alfred Chen, Kevin Fu, and Zhuoqing Morley Mao. Adversarial Sensor Attack on LiDAR-based Perception in Autonomous Driving. In Proceedings of the 26th ACM Conference on Computer and Communications Security (CCS’19), London, UK, November 2019 pdf
  • Yuxin Wen, Jiehong Lin, Ke Chen, and Kui Jia. Geometryaware generation of adversarial and cooperative point clouds. CoRR, abs/1912.11171, 2019. pdf

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published