mlsanityData to 14 Oct 2026

Exposing Deep Fakes Using Inconsistent Head Poses

arXiv 1811.00661 ↗First posted 1 Nov 2018cs.CVcited by 297

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Abstract (arXiv)

In this paper, we propose a new method to expose AI-generated fake face images or videos (commonly known as the Deep Fakes). Our method is based on the observations that Deep Fakes are created by splicing synthesized face region into the original image, and in doing so, introducing errors that can be revealed when 3D head poses are estimated from the face images. We perform experiments to demonstrate this phenomenon and further develop a classification method based on this cue. Using features based on this cue, an SVM classifier is evaluated using a set of real face images and Deep Fakes.

Key facts. Cited by 297 papers in the map (data through 14 Oct 2026). First posted on arXiv 1 Nov 2018.

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Citing papers per year: 2021: 65; 2022: 58; 2023: 54; 2024: 44; 2025: 47; 2026: 29.

297 papers.

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  1. 2021Multi-attentional Deepfake Detectioncited by 341
  2. 2022Detecting Deepfakes with Self-Blended Imagescited by 338
  3. 2023GenImage: A Million-Scale Benchmark for Detecting AI-Generated Imagecited by 321
  4. 2021Spatial-Phase Shallow Learning: Rethinking Face Forgery Detection in Frequency Domaincited by 244
  5. 2021WildDeepfake: A Challenging Real-World Dataset for Deepfake Detectioncited by 209
  6. 2021FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Datasetcited by 181
  7. 2023UCF: Uncovering Common Features for Generalizable Deepfake Detectioncited by 180
  8. 2022Self-supervised Learning of Adversarial Example: Towards Good Generalizations for Deepfake Detectioncited by 173
  9. 2023DeepfakeBench: A Comprehensive Benchmark of Deepfake Detectioncited by 166
  10. 2021Frequency-aware Discriminative Feature Learning Supervised by Single-Center Loss for Face Forgery Detectioncited by 134
  11. 2022Leveraging Real Talking Faces via Self-Supervision for Robust Forgery Detectioncited by 130
  12. 2024DF40: Toward Next-Generation Deepfake Detectioncited by 129
38 more
  1. 2023Transcending Forgery Specificity with Latent Space Augmentation for Generalizable Deepfake Detectioncited by 127
  2. 2021ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysiscited by 126
  3. 2022Implicit Identity Leakage: The Stumbling Block to Improving Deepfake Detection Generalizationcited by 123
  4. 2021M2TR: Multi-modal Multi-scale Transformers for Deepfake Detectioncited by 114
  5. 2021One Shot Face Swapping on Megapixelscited by 105
  6. 2021Dual Contrastive Learning for General Face Forgery Detectioncited by 100
  7. 2023TALL: Thumbnail Layout for Deepfake Video Detectioncited by 100
  8. 2022Protecting Celebrities from DeepFake with Identity Consistency Transformercited by 95
  9. 2021Spatiotemporal Inconsistency Learning for DeepFake Video Detectioncited by 88
  10. 2021Face Forensics in the Wildcited by 87
  11. 2021Deepfakes Generation and Detection: State-of-the-art, open challenges, countermeasures, and way forwardcited by 82
  12. 2021Combining EfficientNet and Vision Transformers for Video Deepfake Detectioncited by 82
  13. 2021KoDF: A Large-scale Korean DeepFake Detection Datasetcited by 80
  14. 2023AV-Deepfake1M: A Large-Scale LLM-Driven Audio-Visual Deepfake Datasetcited by 80
  15. 2022FrePGAN: Robust Deepfake Detection Using Frequency-level Perturbationscited by 75
  16. 2022UIA-ViT: Unsupervised Inconsistency-Aware Method based on Vision Transformer for Face Forgery Detectioncited by 69
  17. 2024Deepfake Generation and Detection: A Benchmark and Surveycited by 67
  18. 2023BlendFace: Re-designing Identity Encoders for Face-Swappingcited by 66
  19. 2021BiHPF: Bilateral High-Pass Filters for Robust Deepfake Detectioncited by 60
  20. 2021Exploiting Fine-grained Face Forgery Clues via Progressive Enhancement Learningcited by 60
  21. 2024AVFF: Audio-Visual Feature Fusion for Video Deepfake Detectioncited by 59
  22. 2024Generalizing Deepfake Video Detection with Plug-and-Play: Video-Level Blending and Spatiotemporal Adapter Tuningcited by 59
  23. 2021Deepfake Detection by Human Crowds, Machines, and Machine-informed Crowdscited by 58
  24. 2021Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Imagescited by 58
  25. 2021Improving the Efficiency and Robustness of Deepfakes Detection through Precise Geometric Featurescited by 57
  26. 2021Countering Malicious DeepFakes: Survey, Battleground, and Horizoncited by 56
  27. 2021OpenForensics: Large-Scale Challenging Dataset For Multi-Face Forgery Detection And Segmentation In-The-Wildcited by 50
  28. 2022Deepfake Detection: A Comprehensive Survey from the Reliability Perspectivecited by 50
  29. 2023Beyond the Prior Forgery Knowledge: Mining Critical Clues for General Face Forgery Detectioncited by 50
  30. 2022SeeABLE: Soft Discrepancies and Bounded Contrastive Learning for Exposing Deepfakescited by 49
  31. 2021Eyes Tell All: Irregular Pupil Shapes Reveal GAN-generated Facescited by 48
  32. 2022A Continual Deepfake Detection Benchmark: Dataset, Methods, and Essentialscited by 45
  33. 2021FReTAL: Generalizing Deepfake Detection using Knowledge Distillation and Representation Learningcited by 44
  34. 2022Voice-Face Homogeneity Tells Deepfakecited by 44
  35. 2023SepMark: Deep Separable Watermarking for Unified Source Tracing and Deepfake Detectioncited by 44
  36. 2023Glitch in the Matrix: A Large Scale Benchmark for Content Driven Audio-Visual Forgery Detection and Localizationcited by 43
  37. 2022Delving into Sequential Patches for Deepfake Detectioncited by 41
  38. 2025Rethinking Vision-Language Model in Face Forensics: Multi-Modal Interpretable Forged Face Detectorcited by 40

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