mlsanityData to 7 Oct 2026

MVSS-Net: Multi-View Multi-Scale Supervised Networks for Image Manipulation Detection

arXiv 2112.08935 ↗First posted 16 Dec 2021cs.CV cs.AIcited by 117

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Abstract (arXiv)

As manipulating images by copy-move, splicing and/or inpainting may lead to misinterpretation of the visual content, detecting these sorts of manipulations is crucial for media forensics. Given the variety of possible attacks on the content, devising a generic method is nontrivial. Current deep learning based methods are promising when training and test data are well aligned, but perform poorly on independent tests. Moreover, due to the absence of authentic test images, their image-level detection specificity is in doubt. The key question is how to design and train a deep neural network capable of learning generalizable features sensitive to manipulations in novel data, whilst specific to prevent false alarms on the authentic. We propose multi-view feature learning to jointly exploit tampering boundary artifacts and the noise view of the input image. As both clues are meant to be semantic-agnostic, the learned features are thus generalizable. For effectively learning from authentic images, we train with multi-scale (pixel / edge / image) supervision. We term the new network MVSS-Net and its enhanced version MVSS-Net++. Experiments are conducted in both within-dataset and cross-dataset scenarios, showing that MVSS-Net++ performs the best, and exhibits better robustness against JPEG compression, Gaussian blur and screenshot based image re-capturing.

Key facts. Cited by 117 papers in the map (data through 7 Oct 2026). Builds on 23 of its 56 references that are in the map. First posted on arXiv 16 Dec 2021.

Builds on

23 of 56 references.

References · 23

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11 more
  1. 2020Media Forensics and DeepFakes: an overviewcited by 208
  2. 2018Learning Rich Features for Image Manipulation Detectioncited by 154
  3. 2018Learning a Discriminative Feature Network for Semantic Segmentationcited by 114
  4. 2021Image Manipulation Detection by Multi-View Multi-Scale Supervisioncited by 111
  5. 2020SPAN: Spatial Pyramid Attention Network forImage Manipulation Localizationcited by 92
  6. 2017Image Splicing Localization Using A Multi-Task Fully Convolutional Network (MFCN)cited by 64
  7. 2019Hybrid LSTM and Encoder-Decoder Architecture for Detection of Image Forgeriescited by 59
  8. 2018Generate, Segment and Refine: Towards Generic Manipulation Segmentationcited by 33
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 20; 2024: 23; 2025: 34; 2026: 38.

117 papers.

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  1. 2023Hierarchical Fine-Grained Image Forgery Detection and Localizationcited by 134
  2. 2022TruFor: Leveraging all-round clues for trustworthy image forgery detection and localizationcited by 130
  3. 2024FakeShield: Explainable Image Forgery Detection and Localization via Multi-modal Large Language Modelscited by 111
  4. 2023EditGuard: Versatile Image Watermarking for Tamper Localization and Copyright Protectioncited by 109
  5. 2024SIDA: Social Media Image Deepfake Detection, Localization and Explanation with Large Multimodal Modelcited by 107
  6. 2023AutoSplice: A Text-prompt Manipulated Image Dataset for Media Forensicscited by 46
  7. 2023IML-ViT: Benchmarking Image Manipulation Localization by Vision Transformercited by 42
  8. 2024IMDL-BenCo: A Comprehensive Benchmark and Codebase for Image Manipulation Detection & Localizationcited by 42
  9. 2024OmniGuard: Hybrid Manipulation Localization via Augmented Versatile Deep Image Watermarkingcited by 35
  10. 2023Pixel-Inconsistency Modeling for Image Manipulation Localizationcited by 33
  11. 2025VideoShield: Regulating Diffusion-based Video Generation Models via Watermarkingcited by 32
  12. 2023Towards Generic Image Manipulation Detection with Weakly-Supervised Self-Consistency Learningcited by 23
38 more
  1. 2023Pre-training-free Image Manipulation Localization through Non-Mutually Exclusive Contrastive Learningcited by 23
  2. 2023Toward Real Text Manipulation Detection: New Dataset and New Solutioncited by 20
  3. 2024TGIF: Text-Guided Inpainting Forgery Datasetcited by 20
  4. 2025Toward Generalizable Forgery Detection and Reasoningcited by 20
  5. 2024GIM: A Million-scale Benchmark for Generative Image Manipulation Detection and Localizationcited by 19
  6. 2024Language-guided Hierarchical Fine-grained Image Forgery Detection and Localizationcited by 16
  7. 2025Zooming In on Fakes: A Novel Dataset for Localized AI-Generated Image Detection with Forgery Amplification Approachcited by 16
  8. 2023The Age of Synthetic Realities: Challenges and Opportunitiescited by 15
  9. 2023Effective Image Tampering Localization via Enhanced Transformer and Co-attention Fusioncited by 15
  10. 2024Exploring Multi-view Pixel Contrast for General and Robust Image Forgery Localizationcited by 15
  11. 2023Rethinking Image Forgery Detection via Soft Contrastive Learning and Unsupervised Clusteringcited by 12
  12. 2023UPOCR: Towards Unified Pixel-Level OCR Interfacecited by 12
  13. 2024Harmfully Manipulated Images Matter in Multimodal Misinformation Detectioncited by 9
  14. 2025UniShield: An Adaptive Multi-Agent Framework for Unified Forgery Image Detection and Localizationcited by 9
  15. 2023Tracing Hyperparameter Dependencies for Model Parsing via Learnable Graph Pooling Networkcited by 8
  16. 2025RAIDX: A Retrieval-Augmented Generation and GRPO Reinforcement Learning Framework for Explainable Deepfake Detectioncited by 8
  17. 2024Fusion Transformer with Object Mask Guidance for Image Forgery Analysiscited by 7
  18. 2024Omni-IML: Towards Unified Image Manipulation Localizationcited by 7
  19. 2025TAG-WM: Tamper-Aware Generative Image Watermarking via Diffusion Inversion Sensitivitycited by 7
  20. 2026Venus-DeFakerOne: Unified Fake Image Detection & Localizationcited by 7
  21. 2023VADER: Video Alignment Differencing and Retrievalcited by 6
  22. 2025M2SFormer: Multi-Spectral and Multi-Scale Attention with Edge-Aware Difficulty Guidance for Image Forgery Localizationcited by 6
  23. 2025ForensicsSAM: Toward Robust and Unified Image Forgery Detection and Localization Resisting to Adversarial Attackcited by 6
  24. 2025ManipShield: A Unified Framework for Image Manipulation Detection, Localization and Explanationcited by 5
  25. 2023Progressive Feedback-Enhanced Transformer for Image Forgery Localizationcited by 4
  26. 2024DA-HFNet: Progressive Fine-Grained Forgery Image Detection and Localization Based on Dual Attentioncited by 4
  27. 2025Reinforced Multi-teacher Knowledge Distillation for Efficient General Image Forgery Detection and Localizationcited by 4
  28. 2025So-Fake: Benchmarking and Explaining Social Media Image Forgery Detectioncited by 4
  29. 2025Weakly-Supervised Image Forgery Localization via Vision-Language Collaborative Reasoning Frameworkcited by 4
  30. 2025StableGuard: Towards Unified Copyright Protection and Tamper Localization in Latent Diffusion Modelscited by 4
  31. 2024PROMPT-IML: Image Manipulation Localization with Pre-trained Foundation Models Through Prompt Tuningcited by 3
  32. 2024Dense Feature Interaction Network for Image Inpainting Localizationcited by 3
  33. 2025InpDiffusion: Image Inpainting Localization via Conditional Diffusion Modelscited by 3
  34. 2025Beyond Fully Supervised Pixel Annotations: Scribble-Driven Weakly-Supervised Framework for Image Manipulation Localizationcited by 3
  35. 2025Webly-Supervised Image Manipulation Localization via Category-Aware Auto-Annotationcited by 3
  36. 2025GS-Checker: Tampering Localization for 3D Gaussian Splattingcited by 3
  37. 2025VizDefender: Unmasking Visualization Tampering through Proactive Localization and Intent Inferencecited by 3
  38. 2024MALT: Multi-scale Action Learning Transformer for Online Action Detectioncited by 2

50 most cited of 117 All 117 (JSON)