mlsanityData to 7 Oct 2026

Two-Stream Neural Networks for Tampered Face Detection

arXiv 1803.11276 ↗First posted 29 Mar 2018cs.CVcited by 125

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Abstract (arXiv)

We propose a two-stream network for face tampering detection. We train GoogLeNet to detect tampering artifacts in a face classification stream, and train a patch based triplet network to leverage features capturing local noise residuals and camera characteristics as a second stream. In addition, we use two different online face swapping applications to create a new dataset that consists of 2010 tampered images, each of which contains a tampered face. We evaluate the proposed two-stream network on our newly collected dataset. Experimental results demonstrate the effectiveness of our method.

Key facts. Cited by 125 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Mar 2018.

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Citing papers per year: 2021: 41; 2022: 35; 2023: 24; 2024: 13; 2025: 10; 2026: 2.

125 papers.

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  1. 2021Multi-attentional Deepfake Detectioncited by 339
  2. 2021Generalizing Face Forgery Detection with High-frequency Featurescited by 261
  3. 2021Spatial-Phase Shallow Learning: Rethinking Face Forgery Detection in Frequency Domaincited by 241
  4. 2021FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Datasetcited by 179
  5. 2023UCF: Uncovering Common Features for Generalizable Deepfake Detectioncited by 177
  6. 2022Self-supervised Learning of Adversarial Example: Towards Good Generalizations for Deepfake Detectioncited by 172
  7. 2023DeepfakeBench: A Comprehensive Benchmark of Deepfake Detectioncited by 162
  8. 2021Exploring Temporal Coherence for More General Video Face Forgery Detectioncited by 158
  9. 2022Leveraging Real Talking Faces via Self-Supervision for Robust Forgery Detectioncited by 130
  10. 2023Transcending Forgery Specificity with Latent Space Augmentation for Generalizable Deepfake Detectioncited by 126
  11. 2021ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysiscited by 124
  12. 2021M2TR: Multi-modal Multi-scale Transformers for Deepfake Detectioncited by 114
38 more
  1. 2022Protecting Celebrities from DeepFake with Identity Consistency Transformercited by 95
  2. 2023Robustness of AI-Image Detectors: Fundamental Limits and Practical Attackscited by 75
  3. 2024Deepfake Generation and Detection: A Benchmark and Surveycited by 66
  4. 2021Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Imagescited by 58
  5. 2024Generalizing Deepfake Video Detection with Plug-and-Play: Video-Level Blending and Spatiotemporal Adapter Tuningcited by 57
  6. 2021Countering Malicious DeepFakes: Survey, Battleground, and Horizoncited by 56
  7. 2021OpenForensics: Large-Scale Challenging Dataset For Multi-Face Forgery Detection And Segmentation In-The-Wildcited by 50
  8. 2022Deepfake Detection: A Comprehensive Survey from the Reliability Perspectivecited by 48
  9. 2022A Continual Deepfake Detection Benchmark: Dataset, Methods, and Essentialscited by 45
  10. 2021FReTAL: Generalizing Deepfake Detection using Knowledge Distillation and Representation Learningcited by 43
  11. 2023SepMark: Deep Separable Watermarking for Unified Source Tracing and Deepfake Detectioncited by 43
  12. 2022Delving into Sequential Patches for Deepfake Detectioncited by 41
  13. 2021CoReD: Generalizing Fake Media Detection with Continual Representation using Distillationcited by 37
  14. 2021Initiative Defense against Facial Manipulationcited by 36
  15. 2022On Improving Cross-dataset Generalization of Deepfake Detectorscited by 34
  16. 2023UMMAFormer: A Universal Multimodal-adaptive Transformer Framework for Temporal Forgery Localizationcited by 33
  17. 2021Evaluation of an Audio-Video Multimodal Deepfake Dataset using Unimodal and Multimodal Detectorscited by 32
  18. 2021DefakeHop: A Light-Weight High-Performance Deepfake Detectorcited by 31
  19. 2021Unified Detection of Digital and Physical Face Attackscited by 31
  20. 2022Green Learning: Introduction, Examples and Outlookcited by 30
  21. 2021COSMOS: Catching Out-of-Context Misinformation with Self-Supervised Learningcited by 26
  22. 2021TransForensics: Image Forgery Localization with Dense Self-Attentioncited by 26
  23. 2023DeepFake-Adapter: Dual-Level Adapter for DeepFake Detectioncited by 26
  24. 2021TAFIM: Targeted Adversarial Attacks against Facial Image Manipulationscited by 25
  25. 2021Exploring Adversarial Fake Images on Face Manifoldcited by 24
  26. 2022Benchmarking Joint Face Spoofing and Forgery Detection with Visual and Physiological Cuescited by 24
  27. 2023Weakly-supervised deepfake localization in diffusion-generated imagescited by 24
  28. 2021Deepfake Videos in the Wild: Analysis and Detectioncited by 23
  29. 2023Controllable Guide-Space for Generalizable Face Forgery Detectioncited by 21
  30. 2024LampMark: Proactive Deepfake Detection via Training-Free Landmark Perceptual Watermarkscited by 21
  31. 2021DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learningcited by 20
  32. 2022Deepfake Video Detection with Spatiotemporal Dropout Transformercited by 19
  33. 2024ManiFPT: Defining and Analyzing Fingerprints of Generative Modelscited by 18
  34. 2022Exposing Deepfake Face Forgeries with Guided Residualscited by 17
  35. 2021FaceGuard: Proactive Deepfake Detectioncited by 16
  36. 2021Detection and Localization of Facial Expression Manipulationscited by 15
  37. 2021Deepfake Forensics via An Adversarial Gamecited by 15
  38. 2021Watch Those Words: Video Falsification Detection Using Word-Conditioned Facial Motioncited by 15

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