How generative adversarial networks promote the development of intelligent transportation systems: A survey
In current years, the improvement of deep learning has brought about tremendous changes:
As a type of unsupervised deep learning algorithm, generative adversarial networks (GANs) …
As a type of unsupervised deep learning algorithm, generative adversarial networks (GANs) …
A survey of robustness and safety of 2d and 3d deep learning models against adversarial attacks
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 …
applications are deployed in many safe-critical systems, such as autopilot and identity …
A survey on safety-critical driving scenario generation—A methodological perspective
Autonomous driving systems have witnessed significant development during the past years
thanks to the advance in machine learning-enabled sensing and decision-making …
thanks to the advance in machine learning-enabled sensing and decision-making …
Advdo: Realistic adversarial attacks for trajectory prediction
Trajectory prediction is essential for autonomous vehicles (AVs) to plan correct and safe
driving behaviors. While many prior works aim to achieve higher prediction accuracy, few …
driving behaviors. While many prior works aim to achieve higher prediction accuracy, few …
Proxyformer: Proxy alignment assisted point cloud completion with missing part sensitive transformer
Problems such as equipment defects or limited viewpoints will lead the captured point
clouds to be incomplete. Therefore, recovering the complete point clouds from the partial …
clouds to be incomplete. Therefore, recovering the complete point clouds from the partial …
Cat: Closed-loop adversarial training for safe end-to-end driving
Driving safety is a top priority for autonomous vehicles. Orthogonal to prior work handling
accident-prone traffic events by algorithm designs at the policy level, we investigate a …
accident-prone traffic events by algorithm designs at the policy level, we investigate a …
Uncovering the missing pattern: Unified framework towards trajectory imputation and prediction
Trajectory prediction is a crucial undertaking in understanding entity movement or human
behavior from observed sequences. However, current methods often assume that the …
behavior from observed sequences. However, current methods often assume that the …
Synthetic datasets for autonomous driving: A survey
Z Song, Z He, X Li, Q Ma, R Ming, Z Mao… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Autonomous driving techniques have been flourishing in recent years while thirsting for
huge amounts of high-quality data. However, it is difficult for real-world datasets to keep up …
huge amounts of high-quality data. However, it is difficult for real-world datasets to keep up …
Mixsim: A hierarchical framework for mixed reality traffic simulation
The prevailing way to test a self-driving vehicle (SDV) in simulation involves non-reactive
open-loop replay of real world scenarios. However, in order to safely deploy SDVs to the …
open-loop replay of real world scenarios. However, in order to safely deploy SDVs to the …
Safebench: A benchmarking platform for safety evaluation of autonomous vehicles
As shown by recent studies, machine intelligence-enabled systems are vulnerable to test
cases resulting from either adversarial manipulation or natural distribution shifts. This has …
cases resulting from either adversarial manipulation or natural distribution shifts. This has …