mlsanityData to 14 Oct 2026

Implicit Identity Leakage: The Stumbling Block to Improving Deepfake Detection Generalization

arXiv 2210.14457 ↗First posted 26 Oct 2022cs.CVcited by 123

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Abstract (arXiv)

In this paper, we analyse the generalization ability of binary classifiers for the task of deepfake detection. We find that the stumbling block to their generalization is caused by the unexpected learned identity representation on images. Termed as the Implicit Identity Leakage, this phenomenon has been qualitatively and quantitatively verified among various DNNs. Furthermore, based on such understanding, we propose a simple yet effective method named the ID-unaware Deepfake Detection Model to reduce the influence of this phenomenon. Extensive experimental results demonstrate that our method outperforms the state-of-the-art in both in-dataset and cross-dataset evaluation. The code is available at https://github.com/megvii-research/CADDM.

Key facts. Cited by 123 papers in the map (data through 14 Oct 2026). Builds on 63 of its 94 references that are in the map. First posted on arXiv 26 Oct 2022.

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63 of 94 references.

References · 63

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Citing papers per year: 2023: 12; 2024: 45; 2025: 45; 2026: 21.

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  1. 2023UCF: Uncovering Common Features for Generalizable Deepfake Detectioncited by 180
  2. 2023DeepfakeBench: A Comprehensive Benchmark of Deepfake Detectioncited by 166
  3. 2024DF40: Toward Next-Generation Deepfake Detectioncited by 129
  4. 2023Transcending Forgery Specificity with Latent Space Augmentation for Generalizable Deepfake Detectioncited by 127
  5. 2024FakeShield: Explainable Image Forgery Detection and Localization via Multi-modal Large Language Modelscited by 113
  6. 2024Orthogonal Subspace Decomposition for Generalizable AI-Generated Image Detectioncited by 105
  7. 2024LAA-Net: Localized Artifact Attention Network for Quality-Agnostic and Generalizable Deepfake Detectioncited by 89
  8. 2024FFAA: Multimodal Large Language Model based Explainable Open-World Face Forgery Analysis Assistantcited by 61
  9. 2024Exploiting Style Latent Flows for Generalizing Deepfake Video Detectioncited by 59
  10. 2024AVFF: Audio-Visual Feature Fusion for Video Deepfake Detectioncited by 59
  11. 2023Beyond the Prior Forgery Knowledge: Mining Critical Clues for General Face Forgery Detectioncited by 50
  12. 2023Towards General Visual-Linguistic Face Forgery Detectioncited by 45
38 more
  1. 2023Improving Fairness in Deepfake Detectioncited by 40
  2. 2025Rethinking Vision-Language Model in Face Forensics: Multi-Modal Interpretable Forged Face Detectorcited by 40
  3. 2024FKA-Owl: Advancing Multimodal Fake News Detection through Knowledge-Augmented LVLMscited by 38
  4. 2024Towards More General Video-based Deepfake Detection through Facial Component Guided Adaptation for Foundation Modelcited by 38
  5. 2024X2-DFD: A framework for eXplainable and eXtendable Deepfake Detectioncited by 35
  6. 2024Fake It till You Make It: Curricular Dynamic Forgery Augmentations towards General Deepfake Detectioncited by 31
  7. 2024DiffusionFake: Enhancing Generalization in Deepfake Detection via Guided Stable Diffusioncited by 29
  8. 2024MoE-FFD: Mixture of Experts for Generalized and Parameter-Efficient Face Forgery Detectioncited by 27
  9. 2025Exploring Unbiased Deepfake Detection via Token-Level Shuffling and Mixingcited by 27
  10. 2024Revisiting Tampered Scene Text Detection in the Era of Generative AIcited by 21
  11. 2024LampMark: Proactive Deepfake Detection via Training-Free Landmark Perceptual Watermarkscited by 21
  12. 2025Unlocking the Capabilities of Large Vision-Language Models for Generalizable and Explainable Deepfake Detectioncited by 21
  13. 2023Robust Identity Perceptual Watermark Against Deepfake Face Swappingcited by 17
  14. 2024SoK: Systematization and Benchmarking of Deepfake Detectors in a Unified Frameworkcited by 14
  15. 2025FreqDebias: Towards Generalizable Deepfake Detection via Consistency-Driven Frequency Debiasingcited by 14
  16. 2024A Survey of Defenses Against AI-Generated Visual Media: Detection,Disruption, and Authenticationcited by 13
  17. 2025Forensics-Bench: A Comprehensive Forgery Detection Benchmark Suite for Large Vision Language Modelscited by 13
  18. 2025Beyond Spatial Frequency: Pixel-wise Temporal Frequency-based Deepfake Video Detectioncited by 13
  19. 2024Delocate: Detection and Localization for Deepfake Videos with Randomly-Located Tampered Tracescited by 12
  20. 2024Learning to Discover Forgery Cues for Face Forgery Detectioncited by 11
  21. 2025Dual Frequency Branch Framework with Reconstructed Sliding Windows Attention for AI-Generated Image Detectioncited by 11
  22. 2025TalkingHeadBench: A Multi-Modal Benchmark & Analysis of Talking-Head DeepFake Detectioncited by 11
  23. 2023GenAI Mirage: The Impostor Bias and the Deepfake Detection Challenge in the Era of Artificial Illusionscited by 10
  24. 2024Deepfake Media Generation and Detection in the Generative AI Era: A Survey and Outlookcited by 10
  25. 2025Vulnerability-Aware Spatio-Temporal Learning for Generalizable Deepfake Video Detectioncited by 9
  26. 2024Diffusion Deepfakecited by 8
  27. 2024Fake Artificial Intelligence Generated Contents (FAIGC): A Survey of Theories, Detection Methods, and Opportunitiescited by 8
  28. 2024Semantic Contextualization of Face Forgery: A New Definition, Dataset, and Detection Methodcited by 8
  29. 2024ED4: Explicit Data-level Debiasing for Deepfake Detectioncited by 8
  30. 2025NullSwap: Proactive Identity Cloaking Against Deepfake Face Swappingcited by 8
  31. 2025A Multimodal Deviation Perceiving Framework for Weakly-Supervised Temporal Forgery Localizationcited by 8
  32. 2025Guard Me If You Know Me: Protecting Specific Face-Identity from Deepfakescited by 7
  33. 2025Fair Deepfake Detectors Can Generalizecited by 7
  34. 2024Evolving from Single-modal to Multi-modal Facial Deepfake Detection: Progress and Challengescited by 6
  35. 2024FakeFormer: Efficient Vulnerability-Driven Transformers for Generalisable Deepfake Detectioncited by 6
  36. 2025AvatarShield: Visual Reinforcement Learning for Human-Centric Synthetic Video Detectioncited by 6
  37. 2025CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillationcited by 6
  38. 2025DATA: Multi-Disentanglement based Contrastive Learning for Open-World Semi-Supervised Deepfake Attributioncited by 5

50 most cited of 123 All 123 (JSON)