This paper aims to address the problem of supervised monocular depth estimation. We start
with a meticulous pilot study to demonstrate that the long-range correlation is essential for …

Deep learning has substantially boosted the performance of Monocular Depth Estimation
(MDE), a critical component in fully vision-based autonomous driving (AD) systems (eg …

This paper systematically analyzes the security risks associated with artificial intelligence
(AI) components in autonomous vehicles (AVs). Given the increasing reliance on AI for …

Monocular Depth Estimation (MDE) is a critical component in applications such as
autonomous driving. There are various attacks against MDE networks. These attacks …

In recent years, many deep learning models have been adopted in autonomous driving. At
the same time, these models introduce new vulnerabilities that may compromise the safety …

This paper focuses on learning transferable adversarial examples specifically against
defense models (models to defense adversarial attacks). In particular, we show that a simple …

Thanks to the excellent learning capability of deep convolutional neural networks (CNN),
monocular depth estimation using CNNs has achieved great success in recent years …

Monocular depth estimation (MDE) plays a crucial role in modern autonomous driving (AD)
by facilitating 3-D scene understanding and interaction. While vulnerabilities in deep neural …

Monocular Depth Estimation (MDE) plays a crucial role in vision-based Autonomous Driving
(AD) systems. It utilizes a single-camera image to determine the depth of objects, facilitating …

Recent advances in monocular depth estimation have been made by incorporating natural
language as additional guidance. Although yielding impressive results the impact of the …