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Adversarial_Attack-Defense

Survey and Thesis

  • Devling into Adversarial Transferability on Image Classification: Review, Benchmark, and Evaluation, Xiaosen Wang, Zhijin Ge, Bohan Liu, Zheng Fang, Fengfan Zhou, Ruixuan Zhang, Shaokang Wang, Yuyang Luo [Paper] [Code]

Year 2024

  • [NIPS 2019] Cross-modal learning with adversarial samples. Advances in neural information processing systems, 32. Li, C., Gao, S., Deng, C., Xie, D., & Liu, W. (2019). [Paper]
  • [arXiv:2409.12394] ITPatch: An Invisible and Triggered Physical Adversarial Patch against Traffic Sign Recognition, Shuai Yuan, Hongwei Li, Xingshuo Han, Guowen Xu, Wenbo Jiang, Tao Ni, Qingchuan Zhao, Yuguang Fang [Paper]
  • [NDSS 2025] Revisiting Physical-World Adversarial Attack on Traffic Sign Recognition: A Commercial Systems Perspective, Ningfei Wang, Shaoyuan Xie, Takami Sato, Yunpeng Luo, Kaidi Xu, Qi Alfred Chen [Paper]
CVPR 2024
  • [CVPR 2024] IDGuard: Robust General Identity-centric POI Proactive Defense Against Face Editing Abuse Yunshu Dai, Jianwei Fei, Fangjun Huang [Paper]
  • [CVPR 2024] Nearest is Not Dearest: Towards Practical Defense against Quantization-conditioned Backdoor Attacks [Paper]
  • [CVPR 2024] Revamping Federated Learning Security from a Defender’s Perspective: A Unified Defense with Homomorphic Encrypted Data Space [Paper]
  • [CVPR 2024] Backdoor Defense via Test-Time Detecting and Repairing [Paper]
  • [CVPR 2024] Efficient Model Stealing Defense with Noise Transition Matrix [Paper]
  • [CVPR 2024] Nearest is Not Dearest: Towards Practical Defense against Quantization-conditioned Backdoor Attacks Boheng Li, Yishuo Cai, Haowei Li, Feng Xue, Zhifeng Li, Yiming Li [Paper] [Code]
  • [CVPR 2024] Focus on Hiders: Exploring Hidden Threats for Enhancing Adversarial Training [Paper]
  • [CVPR 2024] Defense without Forgetting: Continual Adversarial Defense with Anisotropic & Isotropic Pseudo Replay [Paper]
  • [CVPR 2024] Revisiting Adversarial Training at Scale [Paper] [Code]
  • [CVPR 2024] Towards Fairness-Aware Adversarial Learning [Paper] [Code]
  • [CVPR 2024] CAD: Photorealistic 3D Generation via Adversarial Distillation [Paper] [Code]
  • [CVPR 2024] Towards Understanding and Improving Adversarial Robustness of Vision Transformers [Paper] [Code]
  • [CVPR 2024] Revisiting Adversarial Training under Long-Tailed Distributions [Paper] [Code]
  • [CVPR 2024] DAP: A Dynamic Adversarial Patch for Evading Person Detectors [Paper]
  • [CVPR 2024] Adversarial Distillation Based on Slack Matching and Attribution Region Alignment [Paper] [Code]
  • [CVPR 2024] Robust Distillation via Untargeted and Targeted Intermediate Adversarial Samples [Paper]
  • [CVPR 2024] Soften to Defend: Towards Adversarial Robustness via Self-Guided Label Refinement [Paper]
  • [CVPR 2024] Robust Image Denoising through Adversarial Frequency Mixup [Paper] [Code]
  • [CVPR 2024] PeerAiD: Improving Adversarial Distillation from a Specialized Peer Tutor [Paper] [Code]
  • [CVPR 2024] Towards Robust 3D Pose Transfer with Adversarial Learning [Paper]
  • [CVPR 2024] Adversarial Backdoor Attack by Naturalistic Data Poisoning on Trajectory Prediction in Autonomous Driving [Paper]
  • [CVPR 2024] Random Entangled Tokens for Adversarially Robust Vision Transformer [Paper]
  • [CVPR 2024] Watermark-embedded Adversarial Examples for Copyright Protection against Diffusion Models [Paper]
  • [CVPR 2024] Boosting Adversarial Transferability by Block Shuffle and Rotation [Paper] [Code]
  • [CVPR 2024] Infrared Adversarial Car Stickers [Paper]
  • [CVPR 2024] One Prompt Word is Enough to Boost Adversarial Robustness for Pre-trained Vision-Language Models [Paper] [Code]
  • [CVPR 2024] Language-Driven Anchors for Zero-Shot Adversarial Robustness [Paper] [Code]
  • [CVPR 2024] DiffAM: Diffusion-based Adversarial Makeup Transfer for Facial Privacy Protection [Paper] [Code]
  • [CVPR 2024] Structured Gradient-based Interpretations via Norm-Regularized Adversarial Training [Paper] [Code]
  • [CVPR 2024] NAPGuard: Towards Detecting Naturalistic Adversarial Patches [Paper] [Code]
  • [CVPR 2024] PAD: Patch-Agnostic Defense against Adversarial Patch Attacks [Paper] [Code]
  • [CVPR 2024] Robust Overftting Does Matter: Test-Time Adversarial Purifcation With FGSM [Paper] [Code]
  • [CVPR 2024] Structure-Guided Adversarial Training of Diffusion Models [Paper]
  • [CVPR 2024] Adversarial Text to Continuous Image Generation [Paper] [Code]
  • [CVPR 2024] ASAM: Boosting Segment Anything Model with Adversarial Tuning [Paper] [Code]
  • [CVPR 2024] Learning to Transform Dynamically for Better Adversarial Transferability [Paper] [Code]
  • [CVPR 2024] Boosting Adversarial Training via Fisher-Rao Norm-based Regularization [Paper] [Code]
  • [CVPR 2024] Pre-trained Model Guided Fine-Tuning for Zero-Shot Adversarial Robustness [Paper] [Code]
  • [CVPR 2024] MimicDiffusion: Purifying Adversarial Perturbation via Mimicking Clean Diffusion Model [Paper] [Code]
  • [CVPR 2024] Dispel Darkness for Better Fusion: A Controllable Visual Enhancer based on Cross-modal Conditional Adversarial Learning [Paper] [Code]
  • [CVPR 2024] Initialization Matters for Adversarial Transfer Learning [Paper] [Code]
  • [CVPR 2024] Adversarial Score Distillation: When score distillation meets GAN [Paper] [Code]
  • [CVPR 2024] MMCert: Provable Defense against Adversarial Attacks to Multi-modal Models [Paper]
  • [CVPR 2024] ACT-Diffusion: Efficient Adversarial Consistency Training for One-step Diffusion Models [Paper] [Code]
  • [CVPR 2024] Hide in Thicket: Generating Imperceptible and Rational Adversarial Perturbations on 3D Point Clouds [Paper] [Code]
  • [CVPR 2024] Ensemble Diversity Facilitates Adversarial Transferability [Paper] [Code]
  • [CVPR 2024] Attack To Defend: Exploiting Adversarial Attacks for Detecting Poisoned Models Samar Fares, Karthik Nandakumar [Paper]
  • [CVPR 2024] MMCert: Provable Defense against Adversarial Attacks to Multi-modal Models Yanting Wang, Hongye Fu, Wei Zou, Jinyuan Jia [Paper]
  • [CVPR 2024] Semantic-Aware Multi-Label Adversarial Attacks Hassan Mahmood, Ehsan Elhamifar [Paper]
  • [CVPR 2024] Strong Transferable Adversarial Attacks via Ensembled Asymptotically Normal Distribution Learning Zhengwei Fang, Rui Wang, Tao Huang, Liping Jing [Paper]
  • [CVPR 2024] Defense Against Adversarial Attacks on No-Reference Image Quality Models with Gradient Norm Regularization Yujia Liu, Chenxi Yang, Dingquan Li, Jianhao Ding, Tingting Jiang [Paper]
  • [CVPR 2024] SlowFormer: Adversarial Attack on Compute and Energy Consumption of Efficient Vision Transformers K L Navaneet, Soroush Abbasi Koohpayegani, Essam Sleiman, Hamed Pirsiavash [Paper]
  • [CVPR 2024] On the Robustness of Large Multimodal Models Against Image Adversarial Attacks Xuanming Cui, Alejandro Aparcedo, Young Kyun Jang, Ser-Nam Lim [Paper]
  • [CVPR 2024] Towards Transferable Targeted 3D Adversarial Attack in the Physical World Yao Huang, Yinpeng Dong, Shouwei Ruan, Xiao Yang, Hang Su, Xingxing Wei [Paper]
  • [CVPR 2024] Improving Transferable Targeted Adversarial Attacks with Model Self-Enhancement Han Wu, Guanyan Ou, Weibin Wu, Zibin Zheng [Paper]
  • [CVPR 2024] Physical 3D Adversarial Attacks against Monocular Depth Estimation in Autonomous Driving Junhao Zheng, Chenhao Lin, Jiahao Sun, Zhengyu Zhao, Qian Li, Chao Shen [Paper]
  • [CVPR 2024] Transferable Structural Sparse Adversarial Attack Via Exact Group Sparsity Training, Di Ming, Peng Ren, Yunlong Wang, Xin Feng [Paper]
ECCV 2024

Year 2023

Year 2022 & Before