mlsanityData to 14 Oct 2026

Deepfake Detection: A Comprehensive Survey from the Reliability Perspective

arXiv 2211.10881 ↗First posted 20 Nov 2022cs.CV cs.MMcited by 50

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Abstract (arXiv)

The mushroomed Deepfake synthetic materials circulated on the internet have raised a profound social impact on politicians, celebrities, and individuals worldwide. In this survey, we provide a thorough review of the existing Deepfake detection studies from the reliability perspective. We identify three reliability-oriented research challenges in the current Deepfake detection domain: transferability, interpretability, and robustness. Moreover, while solutions have been frequently addressed regarding the three challenges, the general reliability of a detection model has been barely considered, leading to the lack of reliable evidence in real-life usages and even for prosecutions on Deepfake-related cases in court. We, therefore, introduce a model reliability study metric using statistical random sampling knowledge and the publicly available benchmark datasets to review the reliability of the existing detection models on arbitrary Deepfake candidate suspects. Case studies are further executed to justify the real-life Deepfake cases including different groups of victims with the help of the reliably qualified detection models as reviewed in this survey. Reviews and experiments on the existing approaches provide informative discussions and future research directions for Deepfake detection.

Key facts. Cited by 50 papers in the map (data through 14 Oct 2026). Builds on 100 of its 192 references that are in the map. First posted on arXiv 20 Nov 2022.

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100 of 192 references.

References · 100

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Citing papers per year: 2023: 1; 2024: 6; 2025: 24; 2026: 19.

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  1. 2025Unlocking the Capabilities of Large Vision-Language Models for Generalizable and Explainable Deepfake Detectioncited by 21
  2. 2025Rethinking Data Protection in the (Generative) Artificial Intelligence Eracited by 18
  3. 2023Robust Identity Perceptual Watermark Against Deepfake Face Swappingcited by 17
  4. 2026How well are open sourced AI-generated image detection models out-of-the-box: A comprehensive benchmark studycited by 15
  5. 2025Methods and Trends in Detecting AI-Generated Images: A Comprehensive Reviewcited by 12
  6. 2024MFCLIP: Multi-modal Fine-grained CLIP for Generalizable Diffusion Face Forgery Detectioncited by 11
  7. 2025NullSwap: Proactive Identity Cloaking Against Deepfake Face Swappingcited by 8
  8. 2024Open-Set Deepfake Detection: A Parameter-Efficient Adaptation Method with Forgery Style Mixturecited by 7
  9. 2025REVEAL: Robust Evolution of Vision-Language Models for Explainable AI-Video Detectioncited by 7
  10. 2025Fair Deepfake Detectors Can Generalizecited by 7
  11. 2025Learning Real Facial Concepts for Independent Deepfake Detectioncited by 6
  12. 2024Is JPEG AI going to change image forensics?cited by 5
38 more
  1. 2025WaveGuard: Robust Deepfake Detection and Source Tracing via Dual-Tree Complex Wavelet and Graph Neural Networkscited by 5
  2. 2025Agent4FaceForgery: Multi-Agent LLM Framework for Realistic Face Forgery Detectioncited by 5
  3. 2024Semantics-Oriented Multitask Learning for DeepFake Detection: A Joint Embedding Approachcited by 4
  4. 2025FaceSwapGuard: Safeguarding Facial Privacy from DeepFake Threats through Identity Obfuscationcited by 4
  5. 2025FractalForensics: Proactive Deepfake Detection and Localization via Fractal Watermarkscited by 4
  6. 2025Towards Generalized Proactive Defense against Face Swapping with Contour-Hybrid Watermarkcited by 4
  7. 2024Generate Any Scene: Scene Graph Driven Data Synthesis for Visual Generation Trainingcited by 3
  8. 2025Where the Devil Hides: Deepfake Detectors Can No Longer Be Trustedcited by 2
  9. 2025Boosting Active Defense Persistence: A Two-Stage Defense Framework Combining Interruption and Poisoning Against Deepfakecited by 2
  10. 2025A Spatial-Frequency Aware Multi-Scale Fusion Network for Real-Time Deepfake Detectioncited by 2
  11. 2026All in One: Unifying Deepfake Detection, Tampering Localization, and Source Tracing with a Robust Landmark-Identity Watermarkcited by 2
  12. 2026RW-Post: Auditable Evidence-Grounded Multimodal Fact-Checking in the Wildcited by 2
  13. 2025Untraceable DeepFakes via Traceable Fingerprint Eliminationcited by 1
  14. 2025Unmasking Facial DeepFakes: A Robust Multiview Detection Framework for Natural Imagescited by 1
  15. 2026Al'em do Desempenho: Um Estudo da Confiabilidade de Detectores de Deepfakescited by 1
  16. 2026Diffusion-Guided Adversarial Perturbation Injection for Generalizable Defense Against Facial Manipulationscited by 1
  17. 2026Towards High Fidelity Face Swapping: A Comprehensive Survey and New Benchmarkcited by 1
  18. 2026Detecting AI-Generated Video: A Vision-Language Dual-View Surveycited by 1
  19. 2024IDRetracor: Towards Visual Forensics Against Malicious Face Swappingcited by 0
  20. 2025Beyond Known Fakes: Generalized Detection of AI-Generated Images via Post-hoc Distribution Alignmentcited by 0
  21. 2025Leveraging Knowledge Graphs and LLMs for Structured Generation of Misinformationcited by 0
  22. 2025Defending Deepfake via Texture Feature Perturbationcited by 0
  23. 2025Disruptive Attacks on Face Swapping via Low-Frequency Perceptual Perturbationscited by 0
  24. 2025Beyond Real versus Fake Towards Intent-Aware Video Analysiscited by 0
  25. 2025FBA2D: Frequency-based Black-box Attack for AI-generated Image Detectioncited by 0
  26. 2025RW-Post: Auditable Evidence-Grounded Multimodal Fact-Checking in the Wildcited by 0
  27. 2026Conditional Uncertainty-Aware Political Deepfake Detection with Stochastic Convolutional Neural Networkscited by 0
  28. 2026Word-Anchored Temporal Forgery Localizationcited by 0
  29. 2026Towards Generalizable Deepfake Detection via Real Distribution Bias Correctioncited by 0
  30. 2026High-Fidelity Face Content Recovery via Tamper-Resilient Versatile Watermarkingcited by 0
  31. 2026Non-identifiability of Explanations from Model Behavior in Deep Networks of Image Authenticity Judgmentscited by 0
  32. 2026M3D-Net: Multi-Modal 3D Facial Feature Reconstruction Network for Deepfake Detectioncited by 0
  33. 2026Whether, Which, and Whose: Solving the Triple Challenge of Deepfake Proactive Forensics in Multi-Face Scenarioscited by 0
  34. 2026Adaptive Equilibrium: Dynamic Weighting Framework for Generalized Interruption of DeepFake Modelscited by 0
  35. 2026Beyond Seeing Is Believing: On Crowdsourced Detection of Audiovisual Deepfakescited by 0
  36. 2026MFVLR: Multi-domain Fine-grained Vision-Language Reconstruction for Generalizable Diffusion Face Forgery Detection and Localizationcited by 0
  37. 2026Interpretable Deepfake Detection in Videos via Explicit Forensic Features and Temporal Modelingcited by 0
  38. 2026Not Every Cue Is Evidence: Cue Supportability for Forensic Distillation in Face Forgery Detectioncited by 0