Deep Learning is the most widely used tool in the contemporary field of computer vision. Its
ability to accurately solve complex problems is employed in vision research to learn deep …

Benefiting from the rapid development of deep learning, 2D and 3D computer vision
applications are deployed in many safe-critical systems, such as autopilot and identity …

Deep learning is at the heart of the current rise of artificial intelligence. In the field of
computer vision, it has become the workhorse for applications ranging from self-driving cars …

Deep neural networks on 3D point cloud data have been widely used in the real world,
especially in safety-critical applications. However, their robustness against corruptions is …

As 3D point cloud analysis has received increasing attention, the insufficient scale of point
cloud datasets and the weak generalization ability of networks become prominent. In this …

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 …

Abstract Graph Convolutional Networks (GCNs) have shown promising results in modeling
graph-structured data. However, they have difficulty with processing digraphs because of …

Abstract 3D point cloud classification has many safety-critical applications such as
autonomous driving and robotic grasping. However, several studies showed that it is …

As an effective way to acquire accurate information about the driving environment, LiDAR
perception has been widely adopted in autonomous driving. The state-of-the-art LiDAR …

Adversarial attack on point clouds plays a vital role in evaluating and improving the
adversarial robustness of 3D deep learning models. Current attack methods are mainly …