Adversarial attacks and defenses in deep learning for image recognition: A survey
In recent years, researches on adversarial attacks and defense mechanisms have obtained
much attention. It's observed that adversarial examples crafted with small malicious …
much attention. It's observed that adversarial examples crafted with small malicious …
Making an invisibility cloak: Real world adversarial attacks on object detectors
We present a systematic study of the transferability of adversarial attacks on state-of-the-art
object detection frameworks. Using standard detection datasets, we train patterns that …
object detection frameworks. Using standard detection datasets, we train patterns that …
A survey on adversarial attacks and defenses for object detection and their applications in autonomous vehicles
Object detection is considered as one of the most important applications of deep learning.
However, the object detection techniques lose their effectiveness and reliability when they …
However, the object detection techniques lose their effectiveness and reliability when they …
T-sea: Transfer-based self-ensemble attack on object detection
Compared to query-based black-box attacks, transfer-based black-box attacks do not
require any information of the attacked models, which ensures their secrecy. However, most …
require any information of the attacked models, which ensures their secrecy. However, most …
Transferable adversarial attacks for image and video object detection
Adversarial examples have been demonstrated to threaten many computer vision tasks
including object detection. However, the existing attacking methods for object detection have …
including object detection. However, the existing attacking methods for object detection have …
Universal physical camouflage attacks on object detectors
In this paper, we study physical adversarial attacks on object detectors in the wild. Previous
works mostly craft instance-dependent perturbations only for rigid or planar objects. To this …
works mostly craft instance-dependent perturbations only for rigid or planar objects. To this …
Towards adversarially robust object detection
Object detection is an important vision task and has emerged as an indispensable
component in many vision system, rendering its robustness as an increasingly important …
component in many vision system, rendering its robustness as an increasingly important …
Threatening patch attacks on object detection in optical remote sensing images
X Sun, G Cheng, L Pei, H Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Advanced patch attacks (PAs) on object detection in natural images have pointed out the
great safety vulnerability in methods based on deep neural networks (DNNs). However, little …
great safety vulnerability in methods based on deep neural networks (DNNs). However, little …
Exploring adversarial robustness of multi-sensor perception systems in self driving
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 …
complementary inputs such as LiDAR with images. In isolation, 2D images have been found …
Spark: Spatial-aware online incremental attack against visual tracking
Adversarial attacks of deep neural networks have been intensively studied on image, audio,
and natural language classification tasks. Nevertheless, as a typical while important real …
and natural language classification tasks. Nevertheless, as a typical while important real …