The rise and potential of large language model based agents: A survey
For a long time, researchers have sought artificial intelligence (AI) that matches or exceeds
human intelligence. AI agents, which are artificial entities capable of sensing the …
human intelligence. AI agents, which are artificial entities capable of sensing the …
Advances in adversarial attacks and defenses in computer vision: A survey
Deep Learning is the most widely used tool in the contemporary field of computer vision. Its
ability to accurately solve complex problems is employed in vision research to learn deep …
ability to accurately solve complex problems is employed in vision research to learn deep …
Naturalistic physical adversarial patch for object detectors
Most prior works on physical adversarial attacks mainly focus on the attack performance but
seldom enforce any restrictions over the appearance of the generated adversarial patches …
seldom enforce any restrictions over the appearance of the generated adversarial patches …
Physical attack on monocular depth estimation with optimal adversarial patches
Deep learning has substantially boosted the performance of Monocular Depth Estimation
(MDE), a critical component in fully vision-based autonomous driving (AD) systems (eg …
(MDE), a critical component in fully vision-based autonomous driving (AD) systems (eg …
Adversarial texture for fooling person detectors in the physical world
Nowadays, cameras equipped with AI systems can capture and analyze images to detect
people automatically. However, the AI system can make mistakes when receiving …
people automatically. However, the AI system can make mistakes when receiving …
EV AA - Exchange Vanishing Adversarial Attack on LiDAR Point Clouds in Autonomous Vehicles
C Vishnu, J Khandelwal, CK Mohan… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In addition to red-green-blue (RGB) camera sensors, light detection and ranging (LiDAR)
plays an important role in autonomous vehicles (AVs) to perceive their surroundings. Deep …
plays an important role in autonomous vehicles (AVs) to perceive their surroundings. Deep …
Threat of adversarial attacks on deep learning in computer vision: A survey
Deep learning is at the heart of the current rise of artificial intelligence. In the field of
computer vision, it has become the workhorse for applications ranging from self-driving cars …
computer vision, it has become the workhorse for applications ranging from self-driving cars …
When does contrastive learning preserve adversarial robustness from pretraining to finetuning?
Contrastive learning (CL) can learn generalizable feature representations and achieve state-
of-the-art performance of downstream tasks by finetuning a linear classifier on top of it …
of-the-art performance of downstream tasks by finetuning a linear classifier on top of it …
Making an invisibility cloak: Real world adversarial attacks on object detectors
Z Wu, SN Lim, LS Davis, T Goldstein - … , Glasgow, UK, August 23–28, 2020 …, 2020 - Springer
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 …
Adversarial camouflage: Hiding physical-world attacks with natural styles
Deep neural networks (DNNs) are known to be vulnerable to adversarial examples. Existing
works have mostly focused on either digital adversarial examples created via small and …
works have mostly focused on either digital adversarial examples created via small and …