Physical adversarial attack meets computer vision: A decade survey
Despite the impressive achievements of Deep Neural Networks (DNNs) in computer vision,
their vulnerability to adversarial attacks remains a critical concern. Extensive research has …
their vulnerability to adversarial attacks remains a critical concern. Extensive research has …
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 …
Shadows can be dangerous: Stealthy and effective physical-world adversarial attack by natural phenomenon
Y Zhong, X Liu, D Zhai, J Jiang… - Proceedings of the IEEE …, 2022 - openaccess.thecvf.com
Estimating the risk level of adversarial examples is essential for safely deploying machine
learning models in the real world. One popular approach for physical-world attacks is to …
learning models in the real world. One popular approach for physical-world attacks is to …
Rfla: A stealthy reflected light adversarial attack in the physical world
Physical adversarial attacks against deep neural networks (DNNs) have recently gained
increasing attention. The current mainstream physical attacks use printed adversarial …
increasing attention. The current mainstream physical attacks use printed adversarial …
Physically realizable natural-looking clothing textures evade person detectors via 3d modeling
Recent works have proposed to craft adversarial clothes for evading person detectors, while
they are either only effective at limited viewing angles or very conspicuous to humans. We …
they are either only effective at limited viewing angles or very conspicuous to humans. We …
A survey on physical adversarial attack in computer vision
Over the past decade, deep learning has revolutionized conventional tasks that rely on hand-
craft feature extraction with its strong feature learning capability, leading to substantial …
craft feature extraction with its strong feature learning capability, leading to substantial …
Towards more practical threat models in artificial intelligence security
Recent works have identified a gap between research and practice in artificial intelligence
security: threats studied in academia do not always reflect the practical use and security …
security: threats studied in academia do not always reflect the practical use and security …
Physical hijacking attacks against object trackers
Modern autonomous systems rely on both object detection and object tracking in their visual
perception pipelines. Although many recent works have attacked the object detection …
perception pipelines. Although many recent works have attacked the object detection …
Physical-world optical adversarial attacks on 3d face recognition
The success rate of current adversarial attacks remains low on real-world 3D face
recognition tasks because the 3D-printing attacks need to meet the requirement that the …
recognition tasks because the 3D-printing attacks need to meet the requirement that the …
Physical adversarial attacks for camera-based smart systems: Current trends, categorization, applications, research challenges, and future outlook
A Guesmi, MA Hanif, B Ouni, M Shafique - IEEE Access, 2023 - ieeexplore.ieee.org
Deep Neural Networks (DNNs) have shown impressive performance in computer vision
tasks; however, their vulnerability to adversarial attacks raises concerns regarding their …
tasks; however, their vulnerability to adversarial attacks raises concerns regarding their …