Imagen de Portada

Trans-defense: Transformer-based Denoiser for Adversarial Defense with Spatial-Frequency Domain Representation

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Pramanick, Alik, Bansal, Mayank, Srivastava, Utkarsh, Ghosh, Suklav, Sur, Arijit
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

C-LEAD: Contrastive Learning for Enhanced Adversarial Defense
por: Ghosh, Suklav, et al.
Publicado: (2025)

ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer
por: Pramanick, Alik, et al.
Publicado: (2024)

A Generative Adversarial Approach to Adversarial Attacks Guided by Contrastive Language-Image Pre-trained Model
por: Soor, Sampriti, et al.
Publicado: (2025)

Harnessing Multi-resolution and Multi-scale Attention for Underwater Image Restoration
por: Pramanick, Alik, et al.
Publicado: (2024)

Segmentation of tibiofemoral joint tissues from knee MRI using MtRA-Unet and incorporating shape information: Data from the Osteoarthritis Initiative
por: Daydar, Akshay, et al.
Publicado: (2024)

DGSSM: Diffusion guided state-space models for multimodal salient object detection
por: Ghosh, Suklav, et al.
Publicado: (2026)

Universal Adversarial Suffixes Using Calibrated Gumbel-Softmax Relaxation
por: Soor, Sampriti, et al.
Publicado: (2025)

Evaluating Adversarial Robustness in the Spatial Frequency Domain
por: Liao, Keng-Hsin, et al.
Publicado: (2024)

Universal Adversarial Suffixes for Language Models Using Reinforcement Learning with Calibrated Reward
por: Soor, Sampriti, et al.
Publicado: (2025)

Funnel-HOI: Top-Down Perception for Zero-Shot HOI Detection
por: Sarma, Sandipan, et al.
Publicado: (2025)

RetailKLIP : Finetuning OpenCLIP backbone using metric learning on a single GPU for Zero-shot retail product image classification
por: Srivastava, Muktabh Mayank
Publicado: (2023)

Diffusion-based Adversarial Purification from the Perspective of the Frequency Domain
por: Pei, Gaozheng, et al.
Publicado: (2025)

FrequencyCT: Frequency Domain Self-supervised Low-dose CT Denoising
por: Wei, Guoquan, et al.
Publicado: (2026)

Autoencoder-based Denoising Defense against Adversarial Attacks on Object Detection
por: Song, Min Geun, et al.
Publicado: (2025)

Spatial-Frequency Discriminability for Revealing Adversarial Perturbations
por: Wang, Chao, et al.
Publicado: (2023)

Hybrid-Domain Synergistic Transformer for Hyperspectral Image Denoising
por: Li, Haoyue, et al.
Publicado: (2025)

Region of Interest based Medical Image Compression
por: Srivastava, Utkarsh Prakash, et al.
Publicado: (2025)

Boosting Adversarial Transferability Against Defenses via Multi-Scale Transformation
por: Guo, Zihong, et al.
Publicado: (2025)

Fast Adversarial Training with Weak-to-Strong Spatial-Temporal Consistency in the Frequency Domain on Videos
por: Wang, Songping, et al.
Publicado: (2025)

Strong-TransCenter: Improved Multi-Object Tracking based on Transformers with Dense Representations
por: Galor, Amit, et al.
Publicado: (2022)

Zero-Shot Underwater Gesture Recognition
por: Sarma, Sandipan, et al.
Publicado: (2024)

Vision Transformer-based Adversarial Domain Adaptation
por: Li, Yahan, et al.
Publicado: (2024)

Improving Model Generalization by On-manifold Adversarial Augmentation in the Frequency Domain
por: Liu, Chang, et al.
Publicado: (2023)

DatUS^2: Data-driven Unsupervised Semantic Segmentation with Pre-trained Self-supervised Vision Transformer
por: Kumar, Sonal, et al.
Publicado: (2024)

AdvDINO: Domain-Adversarial Self-Supervised Representation Learning for Spatial Proteomics
por: Su, Stella, et al.
Publicado: (2025)

Adversarial Defense Teacher for Cross-Domain Object Detection under Poor Visibility Conditions
por: Wang, Kaiwen, et al.
Publicado: (2024)

DCT-Shield: A Robust Frequency Domain Defense against Malicious Image Editing
por: Bala, Aniruddha, et al.
Publicado: (2025)

Improving Transformation-based Defenses against Adversarial Examples with First-order Perturbations
por: Zhang, Haimin, et al.
Publicado: (2021)

Adversarial Backdoor Defense in CLIP
por: Kuang, Junhao, et al.
Publicado: (2024)

Frequency-Domain Fusion Transformer for Image Inpainting
por: He, Sijin, et al.
Publicado: (2025)

On the Reliability of Vision-Language Models Under Adversarial Frequency-Domain Perturbations
por: Vice, Jordan, et al.
Publicado: (2025)

DenoiseRep: Denoising Model for Representation Learning
por: Xu, Zhengrui, et al.
Publicado: (2024)

TransAdapter: Vision Transformer for Feature-Centric Unsupervised Domain Adaptation
por: Doruk, A. Enes, et al.
Publicado: (2024)

Knee Osteoarthritis Severity Prediction using an Attentive Multi-Scale Deep Convolutional Neural Network
por: Jain, Rohit Kumar, et al.
Publicado: (2021)

Learning Sparse Label Couplings for Multilabel Chest X-Ray Diagnosis
por: Srivastava, Utkarsh Prakash, et al.
Publicado: (2025)

Spatial and Frequency Domain Adaptive Fusion Network for Image Deblurring
por: Gao, Hu, et al.
Publicado: (2025)

Beyond Spatial Explanations: Explainable Face Recognition in the Frequency Domain
por: Huber, Marco, et al.
Publicado: (2024)

Boosting of Implicit Neural Representation-based Image Denoiser
por: Yan, Zipei, et al.
Publicado: (2024)

Universal Adversarial Defense in Remote Sensing Based on Pre-trained Denoising Diffusion Models
por: Yu, Weikang, et al.
Publicado: (2023)

The Unseen Adversaries: Robust and Generalized Defense Against Adversarial Patches
por: Kumar, Vishesh, et al.
Publicado: (2026)