This paper serves as an introduction and overview of the potentially useful models and
methodologies from artificial intelligence (AI) into the field of transportation engineering for …

In autonomous driving (AD), accurate perception is indispensable to achieving safe and
secure driving. Due to its safety-criticality, the security of AD perception has been widely …

In Autonomous Driving (AD), real-time perception is a critical component responsible for
detecting surrounding objects to ensure safe driving. While researchers have extensively …

Modern self-driving perception systems have been shown to improve upon processing
complementary inputs such as LiDAR with images. In isolation, 2D images have been found …

Autonomous vehicles rely on their perception systems to understand their surroundings.
However, the evolution of autonomous navigation technologies has led to new security …

Self-driving cars, believed to be on track to become a seven trillion-dollar industry by 2050,
are likely to be a popular mode of transportation in the near future, as the technology …

Recently, adversarial examples against object detection have been widely studied.
However, it is difficult for these attacks to have an impact on visual perception in …

Denoising probabilistic diffusion models have shown breakthrough performance to generate
more photo-realistic images or human-level illustrations than the prior models such as …

In autonomous vehicles (AVs), a critical stage of perception system is to leverage multi-
modal fusion (MMF) detectors which fuse data from LiDAR (Light Detection and Ranging) …

Stereo matching is a classic challenging problem in computer vision, which has recently
witnessed remarkable progress by Deep Neural Networks (DNNs). This paradigm shift leads …