nowangry/awesome-3D-point-cloud-attacks

List of state of the art papers, code, and other resources

awesome-3D-point-cloud-attacks

List of state of the art papers, code, and other resources focus on 3D point cloud attacks and defense

Attacks

Extending Adversarial Attacks and Defenses to Deep 3D Point Cloud Classifiers.
- [Code]
Adversarial point perturbations on 3D objects. ECCV 2020
- [Code]
PointCloud Saliency Maps. ICCV 2019 drop points attack
- [Code]
LG-GAN: Label Guided Adversarial Network for Flexible Targeted Attack of Point Cloud Based Deep Networks. CVPR 2020
- [Code]
Robust Adversarial Objects against Deep Learning Models. AAAI 2020 knn attack
- [Code]
Self-Robust 3D Point Recognition via Gather-Vector Guidance. CVPR 2020 FGM IFGM MIFGM PGD
On Isometry Robustness of Deep 3D Point Cloud Models Under Adversarial Attacks. CVPR 2020
- [Code]
Adversarial Autoencoders for Generating 3D Point Clouds.
Generating 3D Adversarial Point Clouds. CVPR 2019 CW attack
- [Code]
PU-GAN: a Point Cloud Upsampling Adversarial Network.
- [Code]
3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions.
- [Code]
Adversarial Autoencoders for Compact Representations of 3D Point Clouds.
- [Code]
Physically Realizable Adversarial Examples for LiDAR Object Detection. CVPR 2020
AdvPC: Transferable Adversarial Perturbations on 3D Point Clouds. ECCV 2020
- [Code]
ShapeAdv: Generating Shape-Aware Adversarial 3D Point Clouds.
- [Code]
Robustness of 3D Deep Learning in an Adversarial Setting. CVPR 2019
- [Code]
Nudge Attacks on Point-Cloud DNNs.
Generating Adversarial Surfaces via Band‐Limited Perturbations
Geometry-aware generation of adversarial point clouds. TRAMI
- [Code]
Efficient Joint Gradient Based Attack Against SOR Defense for 3D Point Cloud Classification. ACM MM
Adversarial Objects Against LiDAR Based Autonomous Driving Systems.
Minimal Adversarial Examples for Deep Learning on 3D Point Clouds.
Towards Robust LiDAR-based Perception in Autonomous Driving: General Black-box Adversarial Sensor Attack and Countermeasures.
Geometric Adversarial Attacks and Defenses on 3D Point Clouds. autoencoder attack
- [Code]
Towards Universal Physical Attacks On Cascaded Camera-Lidar 3D Object Detection Models.
Object Removal Attacks on LiDAR-based 3D Object Detectors.
On the Adversarial Robustness of 3D Point Cloud Classification.
Exploring Adversarial Robustness of Multi-Sensor Perception Systems in Self Driving.
Fooling LiDAR Perception via Adversarial Trajectory Perturbation.
- [Code]
PointBA: Towards Backdoor Attacks in 3D Point Cloud.
3D Adversarial Attacks Beyond Point Cloud. mesh attack
- [Code]
Explainability-Aware One Point Attack for Point Cloud Neural Networks. one point attack
- [Code]
Adversarial Attack by Limited Point Cloud Surface Modifications.
PointBA: Towards Backdoor Attacks in 3D Point Cloud. ICCV 2021
A Backdoor Attack Against 3D Point Cloud Classifiers. ICCV 2021
Generating Unrestricted 3D Adversarial Point Clouds.
Local Aggressive Adversarial Attack of 3D point Cloud. ACML oral
- [Code]
Imperceptible Transfer Attack and Defense on 3D Point Cloud Classification.
Attacking Point Cloud Segmentation with Color-only Perturbation segmentation
Dynamics-aware Adversarial Attack of 3D Sparse Convolution Network segmentation
Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks. IEEE S&P
- [Code]
Boosting 3D Adversarial Attacks with Attacking On Frequency AOF attack
- [Code]
Shape-invariant 3D Adversarial Point Clouds. CVPR 2022
- [Code]
Shape Prior Guided Attack: Sparser Perturbations on 3D Point Clouds AAAI 2022
Improving transferability of 3D adversarial attacks with scale and shear transformations SS attack
Isometric 3D Adversarial Examples in the Physical World NeurIPS 2022
Rethinking Perturbation Directions for Imperceptible Adversarial Attacks on Point Clouds IEEE Internet of Things Journal

Defenses