Image de couverture de livre

Filtered-ViT: A Robust Defense Against Multiple Adversarial Patch Attacks

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Khanal, Aja, Faid, Ahmed, Narayan, Apurva
Format:	Preprint
Publié:	2025
Sujets:	Computer Vision and Pattern Recognition Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Concept-Based Masking: A Patch-Agnostic Defense Against Adversarial Patch Attacks
par: Mehrotra, Ayushi, et autres
Publié: (2025)

OmniPatch: A Universal Adversarial Patch for ViT-CNN Cross-Architecture Transfer in Semantic Segmentation
par: Aggarwal, Aarush, et autres
Publié: (2026)

A Real-Time Defense Against Object Vanishing Adversarial Patch Attacks for Object Detection in Autonomous Vehicles
par: Mu, Jaden
Publié: (2024)

STRAP-ViT: Segregated Tokens with Randomized -- Transformations for Defense against Adversarial Patches in ViTs
par: Chattopadhyay, Nandish, et autres
Publié: (2026)

Robust Vision-Language Models via Tensor Decomposition: A Defense Against Adversarial Attacks
par: Patel, Het, et autres
Publié: (2025)

Securing Vision-Language Models with a Robust Encoder Against Jailbreak and Adversarial Attacks
par: Hossain, Md Zarif, et autres
Publié: (2024)

CertMask: Certifiable Defense Against Adversarial Patches via Theoretically Optimal Mask Coverage
par: Lyu, Xuntao, et autres
Publié: (2025)

Purrturbed but Stable: Human-Cat Invariant Representations Across CNNs, ViTs and Self-Supervised ViTs
par: Shah, Arya, et autres
Publié: (2025)

ViT-Lens: Towards Omni-modal Representations
par: Lei, Weixian, et autres
Publié: (2023)

DIFFender: Diffusion-Based Adversarial Defense against Patch Attacks
par: Kang, Caixin, et autres
Publié: (2023)

SFMViT: SlowFast Meet ViT in Chaotic World
par: Lin, Jiaying, et autres
Publié: (2024)

Enhancing Object Detection Robustness: Detecting and Restoring Confidence in the Presence of Adversarial Patch Attacks
par: Kazoom, Roie, et autres
Publié: (2024)

MMeViT: Multi-Modal ensemble ViT for Post-Stroke Rehabilitation Action Recognition
par: Kim, Ye-eun, et autres
Publié: (2025)

HydraViT: Stacking Heads for a Scalable ViT
par: Haberer, Janek, et autres
Publié: (2024)

Embodied Active Defense: Leveraging Recurrent Feedback to Counter Adversarial Patches
par: Wu, Lingxuan, et autres
Publié: (2024)

Dyslexify: A Mechanistic Defense Against Typographic Attacks in CLIP
par: Hufe, Lorenz, et autres
Publié: (2025)

Robust Defense Strategies for Multimodal Contrastive Learning: Efficient Fine-tuning Against Backdoor Attacks
par: Hossain, Md. Iqbal, et autres
Publié: (2025)

Sub-token ViT Embedding via Stochastic Resonance Transformers
par: Lao, Dong, et autres
Publié: (2023)

The Unseen Adversaries: Robust and Generalized Defense Against Adversarial Patches
par: Kumar, Vishesh, et autres
Publié: (2026)

Test-Time Defense Against Adversarial Attacks via Stochastic Resonance of Latent Ensembles
par: Lao, Dong, et autres
Publié: (2025)

CLAMP-ViT: Contrastive Data-Free Learning for Adaptive Post-Training Quantization of ViTs
par: Ramachandran, Akshat, et autres
Publié: (2024)

Robustness Analysis against Adversarial Patch Attacks in Fully Unmanned Stores
par: Na, Hyunsik, et autres
Publié: (2025)

SAC-ViT: Semantic-Aware Clustering Vision Transformer with Early Exit
par: Hu, Youbing, et autres
Publié: (2025)

Hybrid CNN-ViT Framework for Motion-Blurred Scene Text Restoration
par: Rashid, Umar, et autres
Publié: (2025)

ViT-Linearizer: Distilling Quadratic Knowledge into Linear-Time Vision Models
par: Wei, Guoyizhe, et autres
Publié: (2025)

Knowledge Distillation in YOLOX-ViT for Side-Scan Sonar Object Detection
par: Aubard, Martin, et autres
Publié: (2024)

Real-world Adversarial Defense against Patch Attacks based on Diffusion Model
par: Wei, Xingxing, et autres
Publié: (2024)

Adversarial Attack Against Images Classification based on Generative Adversarial Networks
par: Yang, Yahe
Publié: (2024)

Adversarial Vulnerability Transcends Computational Paradigms: Feature Engineering Provides No Defense Against Neural Adversarial Transfer
par: Hsain, Achraf, et autres
Publié: (2026)

Equi-ViT: Rotational Equivariant Vision Transformer for Robust Histopathology Analysis
par: Chen, Fuyao, et autres
Publié: (2026)

ViTs are Everywhere: A Comprehensive Study Showcasing Vision Transformers in Different Domain
par: Mia, Md Sohag, et autres
Publié: (2023)

DFQ-ViT: Data-Free Quantization for Vision Transformers without Fine-tuning
par: Tong, Yujia, et autres
Publié: (2025)

VIVID-Med: LLM-Supervised Structured Pretraining for Deployable Medical ViTs
par: Wang, Xiyao, et autres
Publié: (2026)

LF-ViT: Reducing Spatial Redundancy in Vision Transformer for Efficient Image Recognition
par: Hu, Youbing, et autres
Publié: (2024)

GTP-ViT: Efficient Vision Transformers via Graph-based Token Propagation
par: Xu, Xuwei, et autres
Publié: (2023)

An Intermediate Fusion ViT Enables Efficient Text-Image Alignment in Diffusion Models
par: Hu, Zizhao, et autres
Publié: (2024)

Tiny-ViT: A Compact Vision Transformer for Efficient and Explainable Potato Leaf Disease Classification
par: Mia, Shakil, et autres
Publié: (2026)

Implicit to Explicit Entropy Regularization: Benchmarking ViT Fine-tuning under Noisy Labels
par: Marrium, Maria, et autres
Publié: (2024)

Trio-ViT: Post-Training Quantization and Acceleration for Softmax-Free Efficient Vision Transformer
par: Shi, Huihong, et autres
Publié: (2024)

The Fluorescent Veil: A Stealthy and Effective Physical Adversarial Patch Against Traffic Sign Recognition
par: Yuan, Shuai, et autres
Publié: (2024)