Cover Image

PhysPatch: A Physically Realizable and Transferable Adversarial Patch Attack for Multimodal Large Language Models-based Autonomous Driving Systems

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Guo, Qi, Jia, Xiaojun, Pang, Shanmin, Qin, Simeng, Wang, Lin, Jia, Ju, Liu, Yang, Guo, Qing
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Efficient Generation of Targeted and Transferable Adversarial Examples for Vision-Language Models Via Diffusion Models
by: Guo, Qi, et al.
Published: (2024)

Semantic-Aligned Adversarial Evolution Triangle for High-Transferability Vision-Language Attack
by: Jia, Xiaojun, et al.
Published: (2024)

Transferable Physical-World Adversarial Patches Against Object Detection in Autonomous Driving
by: Zhu, Zihui, et al.
Published: (2026)

Boosting Transferability in Vision-Language Attacks via Diversification along the Intersection Region of Adversarial Trajectory
by: Gao, Sensen, et al.
Published: (2024)

Cross-Model Transferability of Adversarial Patches in Real-time Segmentation for Autonomous Driving
by: Shekhar, Prashant, et al.
Published: (2025)

Towards Physically Realizable Adversarial Attenuation Patch against SAR Object Detection
by: Zhang, Yiming, et al.
Published: (2026)

CAAP: Capture-Aware Adversarial Patch Attacks on Palmprint Recognition Models
by: Liu, Renyang, et al.
Published: (2026)

EmoAttack: Emotion-to-Image Diffusion Models for Emotional Backdoor Generation
by: Wei, Tianyu, et al.
Published: (2024)

GeoShield: Safeguarding Geolocation Privacy from Vision-Language Models via Adversarial Perturbations
by: Liu, Xinwei, et al.
Published: (2025)

PAD: Patch-Agnostic Defense against Adversarial Patch Attacks
by: Jing, Lihua, et al.
Published: (2024)

Comparative Analysis of Patch Attack on VLM-Based Autonomous Driving Architectures
by: Fernandez, David, et al.
Published: (2026)

SwitchPatch: Physical Adversarial Attack Strategy with Switchable Adversarial Objectives
by: Jiang, Hanrui, et al.
Published: (2025)

Adversarial Attacks against Closed-Source MLLMs via Feature Optimal Alignment
by: Jia, Xiaojun, et al.
Published: (2025)

MVPatch: More Vivid Patch for Adversarial Camouflaged Attacks on Object Detectors in the Physical World
by: Zhou, Zheng, et al.
Published: (2023)

When Robots Obey the Patch: Universal Transferable Patch Attacks on Vision-Language-Action Models
by: Lu, Hui, et al.
Published: (2025)

Thermal Topology Collapse: Universal Physical Patch Attacks on Infrared Vision Systems
by: Hu, Chengyin, et al.
Published: (2026)

Exploring the Robustness and Transferability of Patch-Based Adversarial Attacks in Quantized Neural Networks
by: Guesmi, Amira, et al.
Published: (2024)

PapMOT: Exploring Adversarial Patch Attack against Multiple Object Tracking
by: Long, Jiahuan, et al.
Published: (2025)

Digital-to-Physical Transfer of Adversarial Patches for Aerial Vehicle Detection
by: Woo, Jung Heum, et al.
Published: (2026)

Visual Adversarial Attack on Vision-Language Models for Autonomous Driving
by: Zhang, Tianyuan, et al.
Published: (2024)

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches
by: Wang, Zhixiang, et al.
Published: (2024)

Concept-Based Masking: A Patch-Agnostic Defense Against Adversarial Patch Attacks
by: Mehrotra, Ayushi, et al.
Published: (2025)

BB-Patch: BlackBox Adversarial Patch-Attack using Zeroth-Order Optimization
by: Kumar, Satyadwyoom, et al.
Published: (2024)

Towards Powerful and Practical Patch Attacks for 2D Object Detection in Autonomous Driving
by: Cao, Yuxin, et al.
Published: (2025)

Defending Against Physical Adversarial Patch Attacks on Infrared Human Detection
by: Strack, Lukas, et al.
Published: (2023)

Towards Transferable Attacks Against Vision-LLMs in Autonomous Driving with Typography
by: Chung, Nhat, et al.
Published: (2024)

Fight Fire with Fire: Combating Adversarial Patch Attacks using Pattern-randomized Defensive Patches
by: Feng, Jianan, et al.
Published: (2023)

Accelerate 3D Object Detection Models via Zero-Shot Attention Key Pruning
by: Xu, Lizhen, et al.
Published: (2025)

Transferable Physical-World Adversarial Patches Against Pedestrian Detection Models
by: Yan, Shihui, et al.
Published: (2026)

CertMask: Certifiable Defense Against Adversarial Patches via Theoretically Optimal Mask Coverage
by: Lyu, Xuntao, et al.
Published: (2025)

The Outline of Deception: Physical Adversarial Attacks on Traffic Signs Using Edge Patches
by: Ji, Haojie, et al.
Published: (2025)

Generative Adversarial Patches for Physical Attacks on Cross-Modal Pedestrian Re-Identification
by: Su, Yue, et al.
Published: (2024)

Patch of Invisibility: Naturalistic Physical Black-Box Adversarial Attacks on Object Detectors
by: Lapid, Raz, et al.
Published: (2023)

Physical Adversarial Attack on Monocular Depth Estimation via Shape-Varying Patches
by: Zhao, Chenxing, et al.
Published: (2024)

Ti-Patch: Tiled Physical Adversarial Patch for no-reference video quality metrics
by: Leonenkova, Victoria, et al.
Published: (2024)

Dynamic Adversarial Attacks on Autonomous Driving Systems
by: Chahe, Amirhosein, et al.
Published: (2023)

DePatch: Towards Robust Adversarial Patch for Evading Person Detectors in the Real World
by: Cheng, Jikang, et al.
Published: (2024)

Heuristic-Induced Multimodal Risk Distribution Jailbreak Attack for Multimodal Large Language Models
by: Teng, Ma, et al.
Published: (2024)

DiffPAD: Denoising Diffusion-based Adversarial Patch Decontamination
by: Fu, Jia, et al.
Published: (2024)

iPad: Iterative Proposal-centric End-to-End Autonomous Driving
by: Guo, Ke, et al.
Published: (2025)