mlsanityData to 7 Oct 2026

Self-supervised Learning of Adversarial Example: Towards Good Generalizations for Deepfake Detection

arXiv 2203.12208 ↗First posted 23 Mar 2022cs.CVcited by 172

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Abstract (arXiv)

Recent studies in deepfake detection have yielded promising results when the training and testing face forgeries are from the same dataset. However, the problem remains challenging when one tries to generalize the detector to forgeries created by unseen methods in the training dataset. This work addresses the generalizable deepfake detection from a simple principle: a generalizable representation should be sensitive to diverse types of forgeries. Following this principle, we propose to enrich the "diversity" of forgeries by synthesizing augmented forgeries with a pool of forgery configurations and strengthen the "sensitivity" to the forgeries by enforcing the model to predict the forgery configurations. To effectively explore the large forgery augmentation space, we further propose to use the adversarial training strategy to dynamically synthesize the most challenging forgeries to the current model. Through extensive experiments, we show that the proposed strategies are surprisingly effective (see Figure 1), and they could achieve superior performance than the current state-of-the-art methods. Code is available at urlhttps://github.com/liangchen527/SLADD.

Key facts. Cited by 172 papers in the map (data through 7 Oct 2026). Builds on 45 of its 58 references that are in the map. First posted on arXiv 23 Mar 2022.

Builds on

45 of 58 references.

References · 45

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2014Explaining and Harnessing Adversarial Examplescited by 7,287
  3. 2017Towards Deep Learning Models Resistant to Adversarial Attackscited by 6,326
  4. 2016Xception: Deep Learning with Depthwise Separable Convolutionscited by 2,320
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  6. 2019FaceForensics++: Learning to Detect Manipulated Facial Imagescited by 1,095
  7. 2016Adversarial Machine Learning at Scalecited by 934
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  9. 2020Face2Face: Real-time Face Capture and Reenactment of RGB Videoscited by 631
  10. 2020Thinking in Frequency: Face Forgery Detection by Mining Frequency-aware Cluescited by 518
  11. 2019Face X-ray for More General Face Forgery Detectioncited by 469
  12. 2018MesoNet: a Compact Facial Video Forgery Detection Networkcited by 409
33 more
  1. 2017The Effectiveness of Data Augmentation in Image Classification using Deep Learningcited by 368
  2. 2021Multi-attentional Deepfake Detectioncited by 339
  3. 2018Exposing DeepFake Videos By Detecting Face Warping Artifactscited by 318
  4. 2018Exposing Deep Fakes Using Inconsistent Head Posescited by 294
  5. 2020Lips Don't Lie: A Generalisable and Robust Approach to Face Forgery Detectioncited by 286
  6. 2017Data Augmentation Generative Adversarial Networkscited by 278
  7. 2018Additive Margin Softmax for Face Verificationcited by 275
  8. 2021Generalizing Face Forgery Detection with High-frequency Featurescited by 261
  9. 2019Deferred Neural Rendering: Image Synthesis using Neural Texturescited by 253
  10. 2020DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detectioncited by 251
  11. 2021Spatial-Phase Shallow Learning: Rethinking Face Forgery Detection in Frequency Domaincited by 241
  12. 2021High-Fidelity GAN Inversion for Image Attribute Editingcited by 197
  13. 2018Capsule-Forensics: Using Capsule Networks to Detect Forged Images and Videoscited by 180
  14. 2020Learning Self-Consistency for Deepfake Detectioncited by 179
  15. 2022StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGANcited by 169
  16. 2020Two-branch Recurrent Network for Isolating Deepfakes in Videoscited by 161
  17. 2018Synthetic Data Augmentation using GAN for Improved Liver Lesion Classificationcited by 136
  18. 2021Frequency-aware Discriminative Feature Learning Supervised by Single-Center Loss for Face Forgery Detectioncited by 133
  19. 2019Multi-task Learning For Detecting and Segmenting Manipulated Facial Images and Videoscited by 130
  20. 2018Two-Stream Neural Networks for Tampered Face Detectioncited by 125
  21. 2019Adversarial AutoAugmentcited by 111
  22. 2020Learning from Extrinsic and Intrinsic Supervisions for Domain Generalizationcited by 108
  23. 2021Representative Forgery Mining for Fake Face Detectioncited by 108
  24. 2018ForensicTransfer: Weakly-supervised Domain Adaptation for Forgery Detectioncited by 104
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  26. 2021Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Imagescited by 58
  27. 2021Improving the Efficiency and Robustness of Deepfakes Detection through Precise Geometric Featurescited by 57
  28. 2020DeepFake Detection Based on the Discrepancy Between the Face and its Contextcited by 56
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 8; 2023: 34; 2024: 54; 2025: 55; 2026: 21.

172 papers.

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  1. 2023UCF: Uncovering Common Features for Generalizable Deepfake Detectioncited by 177
  2. 2023DeepfakeBench: A Comprehensive Benchmark of Deepfake Detectioncited by 162
  3. 2023Transcending Forgery Specificity with Latent Space Augmentation for Generalizable Deepfake Detectioncited by 126
  4. 2024DF40: Toward Next-Generation Deepfake Detectioncited by 126
  5. 2022Implicit Identity Leakage: The Stumbling Block to Improving Deepfake Detection Generalizationcited by 122
  6. 2024C2P-CLIP: Injecting Category Common Prompt in CLIP to Enhance Generalization in Deepfake Detectioncited by 111
  7. 2024SIDA: Social Media Image Deepfake Detection, Localization and Explanation with Large Multimodal Modelcited by 107
  8. 2024Orthogonal Subspace Decomposition for Generalizable AI-Generated Image Detectioncited by 102
  9. 2023TALL: Thumbnail Layout for Deepfake Video Detectioncited by 100
  10. 2024LAA-Net: Localized Artifact Attention Network for Quality-Agnostic and Generalizable Deepfake Detectioncited by 88
  11. 2023Efficient Region-Aware Neural Radiance Fields for High-Fidelity Talking Portrait Synthesiscited by 72
  12. 2024Exploiting Style Latent Flows for Generalizing Deepfake Video Detectioncited by 58
38 more
  1. 2024Generalizing Deepfake Video Detection with Plug-and-Play: Video-Level Blending and Spatiotemporal Adapter Tuningcited by 57
  2. 2022SeeABLE: Soft Discrepancies and Bounded Contrastive Learning for Exposing Deepfakescited by 49
  3. 2024Can We Leave Deepfake Data Behind in Training Deepfake Detector?cited by 48
  4. 2024CLIPping the Deception: Adapting Vision-Language Models for Universal Deepfake Detectioncited by 47
  5. 2024Exposing the Deception: Uncovering More Forgery Clues for Deepfake Detectioncited by 47
  6. 2023Improved Test-Time Adaptation for Domain Generalizationcited by 45
  7. 2023Towards General Visual-Linguistic Face Forgery Detectioncited by 45
  8. 2023SepMark: Deep Separable Watermarking for Unified Source Tracing and Deepfake Detectioncited by 43
  9. 2024Diffusion Facial Forgery Detectioncited by 41
  10. 2025Rethinking Vision-Language Model in Face Forensics: Multi-Modal Interpretable Forged Face Detectorcited by 38
  11. 2024Towards More General Video-based Deepfake Detection through Facial Component Guided Adaptation for Foundation Modelcited by 37
  12. 2024X2-DFD: A framework for eXplainable and eXtendable Deepfake Detectioncited by 35
  13. 2024Standing on the Shoulders of Giants: Reprogramming Visual-Language Model for General Deepfake Detectioncited by 30
  14. 2024Fake It till You Make It: Curricular Dynamic Forgery Augmentations towards General Deepfake Detectioncited by 30
  15. 2024DiffusionFake: Enhancing Generalization in Deepfake Detection via Guided Stable Diffusioncited by 29
  16. 2025Exploring Unbiased Deepfake Detection via Token-Level Shuffling and Mixingcited by 27
  17. 2023MaLP: Manipulation Localization Using a Proactive Schemecited by 26
  18. 2023DeepFake-Adapter: Dual-Level Adapter for DeepFake Detectioncited by 26
  19. 2023Locate and Verify: A Two-Stream Network for Improved Deepfake Detectioncited by 26
  20. 2024Learning Natural Consistency Representation for Face Forgery Video Detectioncited by 26
  21. 2022Benchmarking Joint Face Spoofing and Forgery Detection with Visual and Physiological Cuescited by 24
  22. 2023DFIL: Deepfake Incremental Learning by Exploiting Domain-invariant Forgery Cluescited by 23
  23. 2023Controllable Guide-Space for Generalizable Face Forgery Detectioncited by 21
  24. 2024Learning Spatiotemporal Inconsistency via Thumbnail Layout for Face Deepfake Detectioncited by 21
  25. 2024FSFM: A Generalizable Face Security Foundation Model via Self-Supervised Facial Representation Learningcited by 21
  26. 2022Mix and Reason: Reasoning over Semantic Topology with Data Mixing for Domain Generalizationcited by 20
  27. 2024Frequency-Aware Deepfake Detection: Improving Generalizability through Frequency Space Learningcited by 20
  28. 2023Domain Generalization via Rationale Invariancecited by 16
  29. 2024GM-DF: Generalized Multi-Scenario Deepfake Detectioncited by 16
  30. 2025From Specificity to Generality: Revisiting Generalizable Artifacts in Detecting Face Deepfakescited by 14
  31. 2025FreqDebias: Towards Generalizable Deepfake Detection via Consistency-Driven Frequency Debiasingcited by 14
  32. 2026Your One-Stop Solution for AI-Generated Video Detectioncited by 13
  33. 2024Delocate: Detection and Localization for Deepfake Videos with Randomly-Located Tampered Tracescited by 12
  34. 2024A Survey of Defenses Against AI-Generated Visual Media: Detection,Disruption, and Authenticationcited by 12
  35. 2025Beyond Spatial Frequency: Pixel-wise Temporal Frequency-based Deepfake Video Detectioncited by 12
  36. 2023Multi-spectral Class Center Network for Face Manipulation Detection and Localizationcited by 11
  37. 2025Do Deepfake Detectors Work in Reality?cited by 11
  38. 2023Reinforced Disentanglement for Face Swapping without Skip Connectioncited by 10

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