Recently, several attempts have demonstrated that 3D deep learning models are as
vulnerable to adversarial example attacks as 2D models. However, these methods are still …

Although many efforts have been made into attack and defense on the 2D image domain in
recent years, few methods explore the vulnerability of 3D models. Existing 3D attackers …

With the maturity of depth sensors, the vulnerability of 3D point cloud models has received
increasing attention in various applications such as autonomous driving and robot …

With the increasing attention in various 3D safety-critical applications, point cloud learning
models have been shown to be vulnerable to adversarial attacks. Although existing 3D …

With the maturity of depth sensors, point clouds have received increasing attention in
various applications such as autonomous driving, robotics, surveillance, etc., while deep …

With the maturity of depth sensors, point clouds have received increasing attention in
various 3D safety-critical applications, while deep point cloud learning models have been …

The use of deep 3D point cloud models in safety-critical applications, such as autonomous
driving, dictates the need to certify the robustness of these models to real-world …

Abstract 3D point cloud models are widely applied in safety-critical scenes, which delivers
an urgent need to obtain more solid proofs to verify the robustness of models. Existing …

With the development of depth sensors and 3D vision, the vulnerability of 3D point cloud
models has garnered heightened concern. Almost all existing 3D attackers are deployed in …

Deep learning models for point clouds have shown to be vulnerable to adversarial attacks,
which have received increasing attention in various safety-critical applications such as …