Improving Visual Quality and Transferability of Adversarial Attacks on Face Recognition Simultaneously with Adversarial Restoration
Fuente:
arXiv
Saved in:
| Main Authors: | Zhou, Fengfan, Ling, Hefei, Shi, Yuxuan, Chen, Jiazhong, Li, Ping |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Improving the Transferability of Adversarial Attacks on Face Recognition with Diverse Parameters Augmentation
by: Zhou, Fengfan, et al.
Published: (2024)
by: Zhou, Fengfan, et al.
Published: (2024)
Improving the JPEG-resistance of Adversarial Attacks on Face Recognition by Interpolation Smoothing
by: Guo, Kefu, et al.
Published: (2024)
by: Guo, Kefu, et al.
Published: (2024)
Adversarial Attacks on Both Face Recognition and Face Anti-spoofing Models
by: Zhou, Fengfan, et al.
Published: (2024)
by: Zhou, Fengfan, et al.
Published: (2024)
Rethinking Impersonation and Dodging Attacks on Face Recognition Systems
by: Zhou, Fengfan, et al.
Published: (2024)
by: Zhou, Fengfan, et al.
Published: (2024)
Real-World Transferable Adversarial Attack on Face-Recognition Systems
by: Kaznacheev, Andrey, et al.
Published: (2025)
by: Kaznacheev, Andrey, et al.
Published: (2025)
Temporal Consistency Constrained Transferable Adversarial Attacks with Background Mixup for Action Recognition
by: Li, Ping, et al.
Published: (2025)
by: Li, Ping, et al.
Published: (2025)
DBDH: A Dual-Branch Dual-Head Neural Network for Invisible Embedded Regions Localization
by: Zhao, Chengxin, et al.
Published: (2024)
by: Zhao, Chengxin, et al.
Published: (2024)
Transferable Adversarial Face Attack with Text Controlled Attribute
by: Li, Wenyun, et al.
Published: (2024)
by: Li, Wenyun, et al.
Published: (2024)
Artificial Immune System of Secure Face Recognition Against Adversarial Attacks
by: Ren, Min, et al.
Published: (2024)
by: Ren, Min, et al.
Published: (2024)
Rethinking the Threat and Accessibility of Adversarial Attacks against Face Recognition Systems
by: Cao, Yuxin, et al.
Published: (2024)
by: Cao, Yuxin, et al.
Published: (2024)
Efficient Image-to-Image Diffusion Classifier for Adversarial Robustness
by: Mei, Hefei, et al.
Published: (2024)
by: Mei, Hefei, et al.
Published: (2024)
A Survey on Physical Adversarial Attacks against Face Recognition Systems
by: Wang, Mingsi, et al.
Published: (2024)
by: Wang, Mingsi, et al.
Published: (2024)
Adversarial Watermarking for Face Recognition
by: Yao, Yuguang, et al.
Published: (2024)
by: Yao, Yuguang, et al.
Published: (2024)
Devling into Adversarial Transferability on Image Classification: Review, Benchmark, and Evaluation
by: Wang, Xiaosen, et al.
Published: (2026)
by: Wang, Xiaosen, et al.
Published: (2026)
Benchmarking Transferable Adversarial Attacks
by: Jin, Zhibo, et al.
Published: (2024)
by: Jin, Zhibo, et al.
Published: (2024)
Human-Imperceptible Physical Adversarial Attack for NIR Face Recognition Models
by: Xie, Songyan, et al.
Published: (2025)
by: Xie, Songyan, et al.
Published: (2025)
Improving Transferability of Adversarial Examples via Bayesian Attacks
by: Li, Qizhang, et al.
Published: (2023)
by: Li, Qizhang, et al.
Published: (2023)
Detecting Adversarial Data using Perturbation Forgery
by: Wang, Qian, et al.
Published: (2024)
by: Wang, Qian, et al.
Published: (2024)
Continual Adversarial Defense
by: Wang, Qian, et al.
Published: (2023)
by: Wang, Qian, et al.
Published: (2023)
Breaking Barriers in Physical-World Adversarial Examples: Improving Robustness and Transferability via Robust Feature
by: Wang, Yichen, et al.
Published: (2024)
by: Wang, Yichen, et al.
Published: (2024)
VQAttack: Transferable Adversarial Attacks on Visual Question Answering via Pre-trained Models
by: Yin, Ziyi, et al.
Published: (2024)
by: Yin, Ziyi, et al.
Published: (2024)
Rethinking Model Ensemble in Transfer-based Adversarial Attacks
by: Chen, Huanran, et al.
Published: (2023)
by: Chen, Huanran, et al.
Published: (2023)
Adversarial Attacks and Detection in Visual Place Recognition for Safer Robot Navigation
by: Malone, Connor, et al.
Published: (2025)
by: Malone, Connor, et al.
Published: (2025)
Improving Transferable Targeted Adversarial Attack via Normalized Logit Calibration and Truncated Feature Mixing
by: Weng, Juanjuan, et al.
Published: (2024)
by: Weng, Juanjuan, et al.
Published: (2024)
Imperceptible Face Forgery Attack via Adversarial Semantic Mask
by: Liu, Decheng, et al.
Published: (2024)
by: Liu, Decheng, et al.
Published: (2024)
Improving the Transferability of Adversarial Examples by Feature Augmentation
by: Wang, Donghua, et al.
Published: (2024)
by: Wang, Donghua, et al.
Published: (2024)
Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples
by: Li, Jian-Wei, et al.
Published: (2025)
by: Li, Jian-Wei, et al.
Published: (2025)
CLIP-Guided Generative Networks for Transferable Targeted Adversarial Attacks
by: Fang, Hao, et al.
Published: (2024)
by: Fang, Hao, et al.
Published: (2024)
Chain of Attack: On the Robustness of Vision-Language Models Against Transfer-Based Adversarial Attacks
by: Xie, Peng, et al.
Published: (2024)
by: Xie, Peng, et al.
Published: (2024)
NAT: Learning to Attack Neurons for Enhanced Adversarial Transferability
by: Nakka, Krishna Kanth, et al.
Published: (2025)
by: Nakka, Krishna Kanth, et al.
Published: (2025)
Investigating Adversarial Robustness against Preprocessing used in Blackbox Face Recognition
by: Croft, Roland, et al.
Published: (2025)
by: Croft, Roland, et al.
Published: (2025)
Exploring the Adversarial Robustness of Face Forgery Detection with Decision-based Black-box Attacks
by: Chen, Zhaoyu, et al.
Published: (2023)
by: Chen, Zhaoyu, et al.
Published: (2023)
Boosting Adversarial Transferability with Spatial Adversarial Alignment
by: Chen, Zhaoyu, et al.
Published: (2025)
by: Chen, Zhaoyu, et al.
Published: (2025)
Probing Unlearned Diffusion Models: A Transferable Adversarial Attack Perspective
by: Han, Xiaoxuan, et al.
Published: (2024)
by: Han, Xiaoxuan, et al.
Published: (2024)
Improving the Transferability of Adversarial Attacks by an Input Transpose
by: Wan, Qing, et al.
Published: (2025)
by: Wan, Qing, et al.
Published: (2025)
Boosting Unconstrained Face Recognition with Targeted Style Adversary
by: Saadabadi, Mohammad Saeed Ebrahimi, et al.
Published: (2024)
by: Saadabadi, Mohammad Saeed Ebrahimi, et al.
Published: (2024)
Improving Adversarial Transferability with Neighbourhood Gradient Information
by: Guo, Haijing, et al.
Published: (2024)
by: Guo, Haijing, et al.
Published: (2024)
ARoFace: Alignment Robustness to Improve Low-Quality Face Recognition
by: Saadabadi, Mohammad Saeed Ebrahimi, et al.
Published: (2024)
by: Saadabadi, Mohammad Saeed Ebrahimi, et al.
Published: (2024)
Enhancing Adversarial Transferability in Visual-Language Pre-training Models via Local Shuffle and Sample-based Attack
by: Liu, Xin, et al.
Published: (2025)
by: Liu, Xin, et al.
Published: (2025)
Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment
by: Jiang, Kaixun, et al.
Published: (2025)
by: Jiang, Kaixun, et al.
Published: (2025)
Similar Items
-
Improving the Transferability of Adversarial Attacks on Face Recognition with Diverse Parameters Augmentation
by: Zhou, Fengfan, et al.
Published: (2024) -
Improving the JPEG-resistance of Adversarial Attacks on Face Recognition by Interpolation Smoothing
by: Guo, Kefu, et al.
Published: (2024) -
Adversarial Attacks on Both Face Recognition and Face Anti-spoofing Models
by: Zhou, Fengfan, et al.
Published: (2024) -
Rethinking Impersonation and Dodging Attacks on Face Recognition Systems
by: Zhou, Fengfan, et al.
Published: (2024) -
Real-World Transferable Adversarial Attack on Face-Recognition Systems
by: Kaznacheev, Andrey, et al.
Published: (2025)