mlsanityData to 7 Oct 2026

Media Forensics and DeepFakes: an overview

arXiv 2001.06564 ↗First posted 18 Jan 2020cs.CVcited by 208

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Abstract (arXiv)

With the rapid progress of recent years, techniques that generate and manipulate multimedia content can now guarantee a very advanced level of realism. The boundary between real and synthetic media has become very thin. On the one hand, this opens the door to a series of exciting applications in different fields such as creative arts, advertising, film production, video games. On the other hand, it poses enormous security threats. Software packages freely available on the web allow any individual, without special skills, to create very realistic fake images and videos. So-called deepfakes can be used to manipulate public opinion during elections, commit fraud, discredit or blackmail people. Potential abuses are limited only by human imagination. Therefore, there is an urgent need for automated tools capable of detecting false multimedia content and avoiding the spread of dangerous false information. This review paper aims to present an analysis of the methods for visual media integrity verification, that is, the detection of manipulated images and videos. Special emphasis will be placed on the emerging phenomenon of deepfakes and, from the point of view of the forensic analyst, on modern data-driven forensic methods. The analysis will help to highlight the limits of current forensic tools, the most relevant issues, the upcoming challenges, and suggest future directions for research.

Key facts. Cited by 208 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Jan 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 32; 2022: 42; 2023: 36; 2024: 19; 2025: 37; 2026: 42.

208 papers.

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  1. 2024MACE: Mass Concept Erasure in Diffusion Modelscited by 298
  2. 2022On the detection of synthetic images generated by diffusion modelscited by 282
  3. 2023Selective Amnesia: A Continual Learning Approach to Forgetting in Deep Generative Modelscited by 175
  4. 2021Are GAN generated images easy to detect? A critical analysis of the state-of-the-artcited by 139
  5. 2023A Recipe for Watermarking Diffusion Modelscited by 136
  6. 2022TruFor: Leveraging all-round clues for trustworthy image forgery detection and localizationcited by 130
  7. 2021MVSS-Net: Multi-View Multi-Scale Supervised Networks for Image Manipulation Detectioncited by 117
  8. 2021Image Manipulation Detection by Multi-View Multi-Scale Supervisioncited by 111
  9. 2022Towards the Detection of Diffusion Model Deepfakescited by 111
  10. 2023TALL: Thumbnail Layout for Deepfake Video Detectioncited by 100
  11. 2021Face Forensics in the Wildcited by 87
  12. 2021Deepfakes Generation and Detection: State-of-the-art, open challenges, countermeasures, and way forwardcited by 82
38 more
  1. 2021Learning JPEG Compression Artifacts for Image Manipulation Detection and Localizationcited by 78
  2. 2021Deepfake Detection by Human Crowds, Machines, and Machine-informed Crowdscited by 58
  3. 2021Countering Malicious DeepFakes: Survey, Battleground, and Horizoncited by 56
  4. 2023Online Detection of AI-Generated Imagescited by 55
  5. 2021Eyes Tell All: Irregular Pupil Shapes Reveal GAN-generated Facescited by 48
  6. 2023AutoSplice: A Text-prompt Manipulated Image Dataset for Media Forensicscited by 46
  7. 2022Audio-Visual Person-of-Interest DeepFake Detectioncited by 43
  8. 2023IML-ViT: Benchmarking Image Manipulation Localization by Vision Transformercited by 42
  9. 2024IMDL-BenCo: A Comprehensive Benchmark and Codebase for Image Manipulation Detection & Localizationcited by 42
  10. 2021Fighting deepfakes by detecting GAN DCT anomaliescited by 39
  11. 2021Detect and Locate: Exposing Face Manipulation by Semantic- and Noise-level Telltalescited by 39
  12. 2024Mesoscopic Insights: Orchestrating Multi-scale & Hybrid Architecture for Image Manipulation Localizationcited by 35
  13. 2021Video Transformer for Deepfake Detection with Incremental Learningcited by 33
  14. 2023Pixel-Inconsistency Modeling for Image Manipulation Localizationcited by 33
  15. 2022GBDF: Gender Balanced DeepFake Dataset Towards Fair DeepFake Detectioncited by 32
  16. 2023Qualitative Failures of Image Generation Models and Their Application in Detecting Deepfakescited by 31
  17. 2022GAN-generated Faces Detection: A Survey and New Perspectivescited by 29
  18. 2023Parents and Children: Distinguishing Multimodal DeepFakes from Natural Imagescited by 29
  19. 2022Face Generation and Editing with StyleGAN: A Surveycited by 27
  20. 2021COSMOS: Catching Out-of-Context Misinformation with Self-Supervised Learningcited by 26
  21. 2021Towards Universal GAN Image Detectioncited by 26
  22. 2021Self-Adversarial Training incorporating Forgery Attention for Image Forgery Localizationcited by 24
  23. 2023Weakly-supervised deepfake localization in diffusion-generated imagescited by 24
  24. 2025CURE: Concept Unlearning via Orthogonal Representation Editing in Diffusion Modelscited by 24
  25. 2021More Real than Real: A Study on Human Visual Perception of Synthetic Facescited by 23
  26. 2024Learning Spatiotemporal Inconsistency via Thumbnail Layout for Face Deepfake Detectioncited by 21
  27. 2021A Survey on Predicting the Factuality and the Bias of News Mediacited by 20
  28. 2024TGIF: Text-Guided Inpainting Forgery Datasetcited by 20
  29. 2022Learning to Immunize Images for Tamper Localization and Self-Recoverycited by 19
  30. 2022Digital and Physical Face Attacks: Reviewing and One Step Furthercited by 17
  31. 2024DeCLIP: Decoding CLIP representations for deepfake localizationcited by 17
  32. 2021Deep Person Generation: A Survey from the Perspective of Face, Pose and Cloth Synthesiscited by 16
  33. 2021A Study of the Human Perception of Synthetic Facescited by 14
  34. 2022On the Exploitation of Deepfake Model Recognitioncited by 14
  35. 2024SoK: Systematization and Benchmarking of Deepfake Detectors in a Unified Frameworkcited by 14
  36. 2023Open Set Synthetic Image Source Attributioncited by 12
  37. 2021Differential Anomaly Detection for Facial Imagescited by 11
  38. 2022Open-Eye: An Open Platform to Study Human Performance on Identifying AI-Synthesized Facescited by 11

50 most cited of 208 All 208 (JSON)