mlsanityData to 7 Oct 2026

FaceForensics: A Large-scale Video Dataset for Forgery Detection in Human Faces

arXiv 1803.09179 ↗First posted 24 Mar 2018cs.CVcited by 118

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Abstract (arXiv)

With recent advances in computer vision and graphics, it is now possible to generate videos with extremely realistic synthetic faces, even in real time. Countless applications are possible, some of which raise a legitimate alarm, calling for reliable detectors of fake videos. In fact, distinguishing between original and manipulated video can be a challenge for humans and computers alike, especially when the videos are compressed or have low resolution, as it often happens on social networks. Research on the detection of face manipulations has been seriously hampered by the lack of adequate datasets. To this end, we introduce a novel face manipulation dataset of about half a million edited images (from over 1000 videos). The manipulations have been generated with a state-of-the-art face editing approach. It exceeds all existing video manipulation datasets by at least an order of magnitude. Using our new dataset, we introduce benchmarks for classical image forensic tasks, including classification and segmentation, considering videos compressed at various quality levels. In addition, we introduce a benchmark evaluation for creating indistinguishable forgeries with known ground truth; for instance with generative refinement models.

Key facts. Cited by 118 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Mar 2018.

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Citing papers per year: 2021: 22; 2022: 21; 2023: 25; 2024: 25; 2025: 14; 2026: 11.

118 papers.

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  1. 2024Latte: Latent Diffusion Transformer for Video Generationcited by 536
  2. 2021StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2cited by 300
  3. 2022CelebV-HQ: A Large-Scale Video Facial Attributes Datasetcited by 246
  4. 2021Neural Head Avatars from Monocular RGB Videoscited by 212
  5. 2023Conditional Image-to-Video Generation with Latent Flow Diffusion Modelscited by 180
  6. 2021A Good Image Generator Is What You Need for High-Resolution Video Synthesiscited by 162
  7. 2022Semantic-Aware Implicit Neural Audio-Driven Video Portrait Generationcited by 119
  8. 2022Generating Long Videos of Dynamic Scenescited by 113
  9. 2021Representative Forgery Mining for Fake Face Detectioncited by 108
  10. 2021One Shot Face Swapping on Megapixelscited by 105
  11. 2023CelebV-Text: A Large-Scale Facial Text-Video Datasetcited by 103
  12. 2023Emotional Speech-Driven Animation with Content-Emotion Disentanglementcited by 98
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  1. 2021Deepfakes Generation and Detection: State-of-the-art, open challenges, countermeasures, and way forwardcited by 82
  2. 2021Towards Discovery and Attribution of Open-world GAN Generated Imagescited by 66
  3. 2021Deepfake Detection by Human Crowds, Machines, and Machine-informed Crowdscited by 58
  4. 2021Countering Malicious DeepFakes: Survey, Battleground, and Horizoncited by 56
  5. 2025AR-Diffusion: Asynchronous Video Generation with Auto-Regressive Diffusioncited by 53
  6. 2023Multimodal Automated Fact-Checking: A Surveycited by 51
  7. 2022Visual Speech-Aware Perceptual 3D Facial Expression Reconstruction from Videoscited by 50
  8. 2024Community Forensics: Using Thousands of Generators to Train Fake Image Detectorscited by 50
  9. 2023HyperReenact: One-Shot Reenactment via Jointly Learning to Refine and Retarget Facescited by 48
  10. 2024Improved Video VAE for Latent Video Diffusion Modelcited by 46
  11. 2022Exploring Frequency Adversarial Attacks for Face Forgery Detectioncited by 45
  12. 2023Learning Personalized High Quality Volumetric Head Avatars from Monocular RGB Videoscited by 44
  13. 2024Deep Learning-based Image and Video Inpainting: A Surveycited by 44
  14. 2021FReTAL: Generalizing Deepfake Detection using Knowledge Distillation and Representation Learningcited by 43
  15. 2023DiffusionAvatars: Deferred Diffusion for High-fidelity 3D Head Avatarscited by 42
  16. 2023LEO: Generative Latent Image Animator for Human Video Synthesiscited by 40
  17. 2023MoStGAN-V: Video Generation with Temporal Motion Stylescited by 37
  18. 2023Evading DeepFake Detectors via Adversarial Statistical Consistencycited by 37
  19. 2021Live Speech Portraits: Real-Time Photorealistic Talking-Head Animationcited by 36
  20. 2024Dyadic Interaction Modeling for Social Behavior Generationcited by 32
  21. 2022Finding Directions in GAN's Latent Space for Neural Face Reenactmentcited by 27
  22. 2023AI-Generated Content (AIGC) for Various Data Modalities: A Surveycited by 25
  23. 2024Matten: Video Generation with Mamba-Attentioncited by 24
  24. 2024A Comprehensive Survey on Human Video Generation: Challenges, Methods, and Insightscited by 24
  25. 2021More Real than Real: A Study on Human Visual Perception of Synthetic Facescited by 23
  26. 2024Gaussian Eigen Models for Human Headscited by 21
  27. 2023Detect Any Deepfakes: Segment Anything Meets Face Forgery Detection and Localizationcited by 20
  28. 2023StyleInV: A Temporal Style Modulated Inversion Network for Unconditional Video Generationcited by 19
  29. 2024Redefining Temporal Modeling in Video Diffusion: The Vectorized Timestep Approachcited by 18
  30. 2022Exposing Deepfake Face Forgeries with Guided Residualscited by 17
  31. 2023Emotional Listener Portrait: Neural Listener Head Generation with Emotioncited by 17
  32. 2024Joker: Conditional 3D Head Synthesis with Extreme Facial Expressionscited by 17
  33. 2024PolyGlotFake: A Novel Multilingual and Multimodal DeepFake Datasetcited by 16
  34. 2021Detection and Localization of Facial Expression Manipulationscited by 15
  35. 2022Testing Human Ability To Detect Deepfake Images of Human Facescited by 15
  36. 2021A Study of the Human Perception of Synthetic Facescited by 14
  37. 2025Synthetic Prior for Few-Shot Drivable Head Avatar Inversioncited by 14
  38. 2022A Review of Deep Learning-based Approaches for Deepfake Content Detectioncited by 12

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