mlsanityData to 14 Oct 2026

Learning Rich Features for Image Manipulation Detection

arXiv 1805.04953 ↗First posted 13 May 2018cs.CVcited by 154

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Abstract (arXiv)

Image manipulation detection is different from traditional semantic object detection because it pays more attention to tampering artifacts than to image content, which suggests that richer features need to be learned. We propose a two-stream Faster R-CNN network and train it endto- end to detect the tampered regions given a manipulated image. One of the two streams is an RGB stream whose purpose is to extract features from the RGB image input to find tampering artifacts like strong contrast difference, unnatural tampered boundaries, and so on. The other is a noise stream that leverages the noise features extracted from a steganalysis rich model filter layer to discover the noise inconsistency between authentic and tampered regions. We then fuse features from the two streams through a bilinear pooling layer to further incorporate spatial co-occurrence of these two modalities. Experiments on four standard image manipulation datasets demonstrate that our two-stream framework outperforms each individual stream, and also achieves state-of-the-art performance compared to alternative methods with robustness to resizing and compression.

Key facts. Cited by 154 papers in the map (data through 14 Oct 2026). First posted on arXiv 13 May 2018.

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Citing papers per year: 2021: 38; 2022: 22; 2023: 35; 2024: 24; 2025: 19; 2026: 16.

154 papers.

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  1. 2023DIRE for Diffusion-Generated Image Detectioncited by 390
  2. 2021Generalizing Face Forgery Detection with High-frequency Featurescited by 262
  3. 2024A Sanity Check for AI-generated Image Detectioncited by 189
  4. 2022A Self-Supervised Descriptor for Image Copy Detectioncited by 176
  5. 2021Exploring Temporal Coherence for More General Video Face Forgery Detectioncited by 159
  6. 2023Hierarchical Fine-Grained Image Forgery Detection and Localizationcited by 134
  7. 2021PSCC-Net: Progressive Spatio-Channel Correlation Network for Image Manipulation Detection and Localizationcited by 133
  8. 2022TruFor: Leveraging all-round clues for trustworthy image forgery detection and localizationcited by 130
  9. 2021MVSS-Net: Multi-View Multi-Scale Supervised Networks for Image Manipulation Detectioncited by 117
  10. 2023Explicit Visual Prompting for Low-Level Structure Segmentationscited by 114
  11. 2021Image Manipulation Detection by Multi-View Multi-Scale Supervisioncited by 111
  12. 2022Protecting Celebrities from DeepFake with Identity Consistency Transformercited by 95
38 more
  1. 2021Learning JPEG Compression Artifacts for Image Manipulation Detection and Localizationcited by 78
  2. 2022ObjectFormer for Image Manipulation Detection and Localizationcited by 78
  3. 2021Making Images Real Again: A Comprehensive Survey on Deep Image Compositioncited by 63
  4. 2023Shadows Don't Lie and Lines Can't Bend! Generative Models don't know Projective Geometry...for nowcited by 61
  5. 2021Countering Malicious DeepFakes: Survey, Battleground, and Horizoncited by 56
  6. 2023Online Detection of AI-Generated Imagescited by 55
  7. 2023Multimodal Automated Fact-Checking: A Surveycited by 53
  8. 2023AutoSplice: A Text-prompt Manipulated Image Dataset for Media Forensicscited by 46
  9. 2021FReTAL: Generalizing Deepfake Detection using Knowledge Distillation and Representation Learningcited by 44
  10. 2023Detecting Images Generated by Deep Diffusion Models using their Local Intrinsic Dimensionalitycited by 44
  11. 2023IML-ViT: Benchmarking Image Manipulation Localization by Vision Transformercited by 44
  12. 2024IMDL-BenCo: A Comprehensive Benchmark and Codebase for Image Manipulation Detection & Localizationcited by 42
  13. 2021Detect and Locate: Exposing Face Manipulation by Semantic- and Noise-level Telltalescited by 39
  14. 2021CoReD: Generalizing Fake Media Detection with Continual Representation using Distillationcited by 37
  15. 2022Learning Second Order Local Anomaly for General Face Forgery Detectioncited by 36
  16. 2021One Detector to Rule Them All: Towards a General Deepfake Attack Detection Frameworkcited by 33
  17. 2023Pixel-Inconsistency Modeling for Image Manipulation Localizationcited by 33
  18. 2021Evaluation of an Audio-Video Multimodal Deepfake Dataset using Unimodal and Multimodal Detectorscited by 32
  19. 2023Contrastive Pseudo Learning for Open-World DeepFake Attributioncited by 27
  20. 2021TransForensics: Image Forgery Localization with Dense Self-Attentioncited by 26
  21. 2021Spatial-Separated Curve Rendering Network for Efficient and High-Resolution Image Harmonizationcited by 25
  22. 2022Bootstrapping Multi-view Representations for Fake News Detectioncited by 25
  23. 2021Self-Adversarial Training incorporating Forgery Attention for Image Forgery Localizationcited by 24
  24. 2023Weakly-supervised deepfake localization in diffusion-generated imagescited by 24
  25. 2023Towards Generic Image Manipulation Detection with Weakly-Supervised Self-Consistency Learningcited by 23
  26. 2023Pre-training-free Image Manipulation Localization through Non-Mutually Exclusive Contrastive Learningcited by 23
  27. 2023Toward Real Text Manipulation Detection: New Dataset and New Solutioncited by 20
  28. 2021TAR: Generalized Forensic Framework to Detect Deepfakes using Weakly Supervised Learningcited by 19
  29. 2022Learning to Immunize Images for Tamper Localization and Self-Recoverycited by 19
  30. 2024GIM: A Million-scale Benchmark for Generative Image Manipulation Detection and Localizationcited by 19
  31. 2022Exposing Deepfake Face Forgeries with Guided Residualscited by 17
  32. 2023EXIF as Language: Learning Cross-Modal Associations Between Images and Camera Metadatacited by 17
  33. 2023Explicit Visual Prompting for Universal Foreground Segmentationscited by 17
  34. 2024Language-guided Hierarchical Fine-grained Image Forgery Detection and Localizationcited by 16
  35. 2021Detection and Localization of Facial Expression Manipulationscited by 15
  36. 2023The Age of Synthetic Realities: Challenges and Opportunitiescited by 15
  37. 2024Exploring Multi-view Pixel Contrast for General and Robust Image Forgery Localizationcited by 15
  38. 2024ForgeryGPT: A Multimodal LLM for Interpretable Image Forgery Detection and Localizationcited by 13

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