activity
20232026
most citedTransferable Adversarial Facial Images for Privacy Protection

2 citations · 7 across the 35 of their papers we have counts for

collaborators
Showing 2024Show all

10 papers · 1 filter

cs.CV2024

Breaking Barriers in Physical-World Adversarial Examples: Improving Robustness and Transferability via Robust Feature

Yichen Wang, Yuxuan Chou, Ziqi Zhou +4

As deep neural networks (DNNs) are widely applied in the physical world, many researches are focusing on physical-world adversarial examples (PAEs), which introduce perturbations t…

cs.CV2024

NumbOD: A Spatial-Frequency Fusion Attack Against Object Detectors

Ziqi Zhou, Bowen Li, Yufei Song +6

With the advancement of deep learning, object detectors (ODs) with various architectures have achieved significant success in complex scenarios like autonomous driving. Previous ad…

cs.RO2024

Robot Collapse: Supply Chain Backdoor Attacks Against VLM-based Robotic Manipulation

Xianlong Wang, Hewen Pan, Hangtao Zhang +8

Robotic manipulation policies are increasingly empowered by \textit{large language models} (LLMs) and \textit{vision-language models} (VLMs), leveraging their understanding and per…

cs.CV2024

Unlearnable 3D Point Clouds: Class-wise Transformation Is All You Need

Xianlong Wang, Minghui Li, Wei Liu +5

Traditional unlearnable strategies have been proposed to prevent unauthorized users from training on the 2D image data. With more 3D point cloud data containing sensitivity informa…

cs.AI2024★ 1 cited

DarkSAM: Fooling Segment Anything Model to Segment Nothing

Ziqi Zhou, Yufei Song, Minghui Li +5

Segment Anything Model (SAM) has recently gained much attention for its outstanding generalization to unseen data and tasks. Despite its promising prospect, the vulnerabilities of…

cs.CV2024★ 2 cited

Transferable Adversarial Facial Images for Privacy Protection

Minghui Li, Jiangxiong Wang, Hao Zhang +3

The success of deep face recognition (FR) systems has raised serious privacy concerns due to their ability to enable unauthorized tracking of users in the digital world. Previous s…

cs.CY2024★ 1 cited

BadRobot: Jailbreaking Embodied LLM Agents in the Physical World

Hangtao Zhang, Chenyu Zhu, Xianlong Wang +9

Embodied AI represents systems where AI is integrated into physical entities. Large Language Model (LLM), which exhibits powerful language understanding abilities, has been extensi…

cs.CR2024

ECLIPSE: Expunging Clean-label Indiscriminate Poisons via Sparse Diffusion Purification

Xianlong Wang, Shengshan Hu, Yechao Zhang +5

Clean-label indiscriminate poisoning attacks add invisible perturbations to correctly labeled training images, thus dramatically reducing the generalization capability of the victi…

cs.CV2024

Detector Collapse: Physical-World Backdooring Object Detection to Catastrophic Overload or Blindness in Autonomous Driving

Hangtao Zhang, Shengshan Hu, Yichen Wang +5

Object detection tasks, crucial in safety-critical systems like autonomous driving, focus on pinpointing object locations. These detectors are known to be susceptible to backdoor a…

cs.CV2024★ 2 cited

Securely Fine-tuning Pre-trained Encoders Against Adversarial Examples

Ziqi Zhou, Minghui Li, Wei Liu +7

With the evolution of self-supervised learning, the pre-training paradigm has emerged as a predominant solution within the deep learning landscape. Model providers furnish pre-trai…