Imagen de Portada

Adversarial Examples in Environment Perception for Automated Driving (Review)

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Yan, Jun, Yin, Huilin
Formato:	Preprint
Publicado:	2025
Materias:	Computer Vision and Pattern Recognition
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Segment-Anything Models Achieve Zero-shot Robustness in Autonomous Driving
por: Yan, Jun, et al.
Publicado: (2024)

Collaborative Perception Datasets for Autonomous Driving: A Review
por: Wang, Naibang, et al.
Publicado: (2025)

WS-DETR: Robust Water Surface Object Detection through Vision-Radar Fusion with Detection Transformer
por: Yin, Huilin, et al.
Publicado: (2025)

AID4AD: Aerial Image Data for Automated Driving Perception
por: Lengerer, Daniel, et al.
Publicado: (2025)

SA-Attack: Speed-adaptive stealthy adversarial attack on trajectory prediction
por: Yin, Huilin, et al.
Publicado: (2024)

How Could Generative AI Support Compliance with the EU AI Act? A Review for Safe Automated Driving Perception
por: Keser, Mert, et al.
Publicado: (2024)

Adversarial Example Defense via Perturbation Grading Strategy
por: Zhu, Shaowei, et al.
Publicado: (2022)

Improving the Transferability of Adversarial Examples by Feature Augmentation
por: Wang, Donghua, et al.
Publicado: (2024)

Collective Perception Datasets for Autonomous Driving: A Comprehensive Review
por: Teufel, Sven, et al.
Publicado: (2024)

Adv3D: Generating 3D Adversarial Examples for 3D Object Detection in Driving Scenarios with NeRF
por: Li, Leheng, et al.
Publicado: (2023)

AdvSwap: Covert Adversarial Perturbation with High Frequency Info-swapping for Autonomous Driving Perception
por: Huang, Yuanhao, et al.
Publicado: (2025)

SegTrans: Transferable Adversarial Examples for Segmentation Models
por: Song, Yufei, et al.
Publicado: (2025)

Utilizing Adversarial Examples for Bias Mitigation and Accuracy Enhancement
por: Shukla, Pushkar, et al.
Publicado: (2024)

Adversarial Example Soups: Improving Transferability and Stealthiness for Free
por: Yang, Bo, et al.
Publicado: (2024)

Adversarial Examples Are Not Real Features
por: Li, Ang, et al.
Publicado: (2023)

Challenger: Affordable Adversarial Driving Video Generation
por: Xu, Zhiyuan, et al.
Publicado: (2025)

Occluded nuScenes: A Multi-Sensor Dataset for Evaluating Perception Robustness in Automated Driving
por: Kumar, Sanjay, et al.
Publicado: (2025)

CapGen:An Environment-Adaptive Generator of Adversarial Patches
por: Li, Chaoqun, et al.
Publicado: (2024)

SCOOTER: A Human Evaluation Framework for Unrestricted Adversarial Examples
por: Fazlija, Dren, et al.
Publicado: (2025)

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples
por: Li, Jian-Wei, et al.
Publicado: (2025)

Towards Adaptive Meta-Gradient Adversarial Examples for Visual Tracking
por: Tian, Wei-Long, et al.
Publicado: (2025)

SD-NAE: Generating Natural Adversarial Examples with Stable Diffusion
por: Lin, Yueqian, et al.
Publicado: (2023)

Can Adversarial Examples Be Parsed to Reveal Victim Model Information?
por: Yao, Yuguang, et al.
Publicado: (2023)

Cloud Adversarial Example Generation for Remote Sensing Image Classification
por: Ma, Fei, et al.
Publicado: (2024)

Defensive Adversarial CAPTCHA: A Semantics-Driven Framework for Natural Adversarial Example Generation
por: Du, Xia, et al.
Publicado: (2025)

Imperceptible Adversarial Examples in the Physical World
por: Xu, Weilin, et al.
Publicado: (2024)

Improving Fast Adversarial Training Paradigm: An Example Taxonomy Perspective
por: Gui, Jie, et al.
Publicado: (2024)

VENOM: Text-driven Unrestricted Adversarial Example Generation with Diffusion Models
por: Kuurila-Zhang, Hui, et al.
Publicado: (2025)

A Survey on Transferability of Adversarial Examples across Deep Neural Networks
por: Gu, Jindong, et al.
Publicado: (2023)

Enhancing Transferability of Targeted Adversarial Examples: A Self-Universal Perspective
por: Peng, Bowen, et al.
Publicado: (2024)

The Ultimate Combo: Boosting Adversarial Example Transferability by Composing Data Augmentations
por: Yun, Zebin, et al.
Publicado: (2023)

Securely Fine-tuning Pre-trained Encoders Against Adversarial Examples
por: Zhou, Ziqi, et al.
Publicado: (2024)

Latent Transfer Attack: Adversarial Examples via Generative Latent Spaces
por: Shaar, Eitan, et al.
Publicado: (2026)

Composing Driving Worlds through Disentangled Control for Adversarial Scenario Generation
por: Zhan, Yifan, et al.
Publicado: (2026)

Reinforced Embodied Active Defense: Exploiting Adaptive Interaction for Robust Visual Perception in Adversarial 3D Environments
por: Yang, Xiao, et al.
Publicado: (2025)

UniDriveVLA: Unifying Understanding, Perception, and Action Planning for Autonomous Driving
por: Li, Yongkang, et al.
Publicado: (2026)

Reversing Skin Cancer Adversarial Examples by Multiscale Diffusive and Denoising Aggregation Mechanism
por: Wang, Yongwei, et al.
Publicado: (2022)

CLIPping the Limits: Finding the Sweet Spot for Relevant Images in Automated Driving Systems Perception Testing
por: Rigoll, Philipp, et al.
Publicado: (2024)

Adversarial Examples are Misaligned in Diffusion Model Manifolds
por: Lorenz, Peter, et al.
Publicado: (2024)

Adversarial Examples Detection with Bayesian Neural Network
por: Li, Yao, et al.
Publicado: (2021)