mlsanityData to 7 Oct 2026

Adversarial Defense by Suppressing High-frequency Components

arXiv 1908.06566 ↗First posted 19 Aug 2019cs.CV cs.LG eess.IVcited by 22

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Abstract (arXiv)

Recent works show that deep neural networks trained on image classification dataset bias towards textures. Those models are easily fooled by applying small high-frequency perturbations to clean images. In this paper, we learn robust image classification models by removing high-frequency components. Specifically, we develop a differentiable high-frequency suppression module based on discrete Fourier transform (DFT). Combining with adversarial training, we won the 5th place in the IJCAI-2019 Alibaba Adversarial AI Challenge. Our code is available online.

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Aug 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 2; 2023: 7; 2024: 9; 2025: 1; 2026: 1.

22 papers.

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  1. 2023A Comprehensive Study on Robustness of Image Classification Models: Benchmarking and Rethinkingcited by 85
  2. 2023Robustness of SAM: Segment Anything Under Corruptions and Beyondcited by 30
  3. 2023Towards Building More Robust Models with Frequency Biascited by 12
  4. 2022Robust Real-World Image Super-Resolution against Adversarial Attackscited by 11
  5. 2021Impact of Spatial Frequency Based Constraints on Adversarial Robustnesscited by 8
  6. 2024Characterizing Model Robustness via Natural Input Gradientscited by 6
  7. 2022Scale-free and Task-agnostic Attack: Generating Photo-realistic Adversarial Patterns with Patch Quilting Generatorcited by 5
  8. 2023Self-supervised Adaptive Pre-training of Multilingual Speech Models for Language and Dialect Identificationcited by 2
  9. 2024Robust width: A lightweight and certifiable adversarial defensecited by 1
  10. 2024DFT-Based Adversarial Attack Detection in MRI Brain Imaging: Enhancing Diagnostic Accuracy in Alzheimer's Case Studiescited by 1
  11. 2021Signal Transformer: Complex-valued Attention and Meta-Learning for Signal Recognitioncited by 0
  12. 2023Enhancing Multilingual Speech Recognition through Language Prompt Tuning and Frame-Level Language Adaptercited by 0
10 more
  1. 2023GMTR: Graph Matching Transformerscited by 0
  2. 2023DarkShot: Lighting Dark Images with Low-Compute and High-Qualitycited by 0
  3. 2024TRLS: A Time Series Representation Learning Framework via Spectrogram for Medical Signal Processingcited by 0
  4. 2024TEN-GUARD: Tensor Decomposition for Backdoor Attack Detection in Deep Neural Networkscited by 0
  5. 2024T-Pixel2Mesh: Combining Global and Local Transformer for 3D Mesh Generation from a Single Imagecited by 0
  6. 2024Strategic Arms with Side Communication Prevail Over Low-Regret MAB Algorithmscited by 0
  7. 2024Towards General Deepfake Detection with Dynamic Curriculumcited by 0
  8. 2024Attr-Int: A Simple and Effective Entity Alignment Framework for Heterogeneous Knowledge Graphscited by 0
  9. 2025Mask6D: Masked Pose Priors For 6D Object Pose Estimationcited by 0
  10. 2026TaFD: Threat-Aware Frequency Decoupling for Adversarial Robustness against Heterogeneous Attackscited by 0