mlsanityData to 14 Oct 2026

RepMix: Representation Mixing for Robust Attribution of Synthesized Images

arXiv 2207.02063 ↗First posted 5 Jul 2022cs.CVcited by 39

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Abstract (arXiv)

Rapid advances in Generative Adversarial Networks (GANs) raise new challenges for image attribution; detecting whether an image is synthetic and, if so, determining which GAN architecture created it. Uniquely, we present a solution to this task capable of 1) matching images invariant to their semantic content; 2) robust to benign transformations (changes in quality, resolution, shape, etc.) commonly encountered as images are re-shared online. In order to formalize our research, a challenging benchmark, Attribution88, is collected for robust and practical image attribution. We then propose RepMix, our GAN fingerprinting technique based on representation mixing and a novel loss. We validate its capability of tracing the provenance of GAN-generated images invariant to the semantic content of the image and also robust to perturbations. We show our approach improves significantly from existing GAN fingerprinting works on both semantic generalization and robustness. Data and code are available at https://github.com/TuBui/image_attribution.

Key facts. Cited by 39 papers in the map (data through 14 Oct 2026). Builds on 42 of its 65 references that are in the map. First posted on arXiv 5 Jul 2022.

Builds on

42 of 65 references.

References · 42

  1. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  2. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  3. 2014Explaining and Harnessing Adversarial Examplescited by 7,364
  4. 2016Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localizationcited by 6,733
  5. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 6,013
  6. 2017mixup: Beyond Empirical Risk Minimizationcited by 5,183
  7. 2014Deep Learning Face Attributes in the Wildcited by 3,693
  8. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,588
  9. 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,988
  10. 2019CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Featurescited by 2,884
  11. 2019Benchmarking Neural Network Robustness to Common Corruptions and Perturbationscited by 2,877
  12. 2016Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Networkcited by 1,908
30 more
  1. 2020The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalizationcited by 1,850
  2. 2018Spectral Normalization for Generative Adversarial Networkscited by 1,636
  3. 2015LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loopcited by 1,355
  4. 2019Semantic Image Synthesis with Spatially-Adaptive Normalizationcited by 1,299
  5. 2018Demystifying MMD GANscited by 1,293
  6. 2021Alias-Free Generative Adversarial Networkscited by 1,184
  7. 2019AugMix: A Simple Data Processing Method to Improve Robustness and Uncertaintycited by 901
  8. 2019CNN-generated images are surprisingly easy to spot... for nowcited by 847
  9. 2021Generalizing to Unseen Domains: A Survey on Domain Generalizationcited by 766
  10. 2018Generative Image Inpainting with Contextual Attentioncited by 580
  11. 2020Leveraging Frequency Analysis for Deep Fake Image Recognitioncited by 504
  12. 2019Detecting and Simulating Artifacts in GAN Fake Imagescited by 293
  13. 2020Artificial Fingerprinting for Generative Models: Rooting Deepfake Attribution in Training Datacited by 201
  14. 2018Do GANs leave artificial fingerprints?cited by 190
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  16. 2017The Cramer Distance as a Solution to Biased Wasserstein Gradientscited by 119
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  18. 2020Responsible Disclosure of Generative Models Using Scalable Fingerprintingcited by 91
  19. 2019Specifying Object Attributes and Relations in Interactive Scene Generationcited by 76
  20. 2021Towards Discovery and Attribution of Open-world GAN Generated Imagescited by 66
  21. 2020SofGAN: A Portrait Image Generator with Dynamic Stylingcited by 65
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  23. 2021Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Imagescited by 58
  24. 2021Beyond the Spectrum: Detecting Deepfakes via Re-Synthesiscited by 44
  25. 2017Image Generation from Sketch Constraint Using Contextual GANcited by 34
  26. 2018Towards Audio to Scene Image Synthesis using Generative Adversarial Networkcited by 23
  27. 2019Texture Mixer: A Network for Controllable Synthesis and Interpolation of Texturecited by 15
  28. 2021OSCAR-Net: Object-centric Scene Graph Attention for Image Attributioncited by 15
  29. 2019ARCHANGEL: Tamper-proofing Video Archives using Temporal Content Hashes on the Blockchaincited by 7
  30. 2021VPN: Video Provenance Network for Robust Content Attributioncited by 7

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Citing papers per year: 2023: 14; 2024: 10; 2025: 7; 2026: 8.

39 papers.

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  1. 2023Hierarchical Fine-Grained Image Forgery Detection and Localizationcited by 134
  2. 2023Online Detection of AI-Generated Imagescited by 55
  3. 2023TrustMark: Universal Watermarking for Arbitrary Resolution Imagescited by 51
  4. 2023Generalizable Synthetic Image Detection via Language-guided Contrastive Learningcited by 49
  5. 2023Evaluating Data Attribution for Text-to-Image Modelscited by 45
  6. 2023PTW: Pivotal Tuning Watermarking for Pre-Trained Image Generatorscited by 37
  7. 2023ArtiFact: A Large-Scale Dataset with Artificial and Factual Images for Generalizable and Robust Synthetic Image Detectioncited by 35
  8. 2023Progressive Open Space Expansion for Open-Set Model Attributioncited by 32
  9. 2023Rethinking Image Editing Detection in the Era of Generative AI Revolutioncited by 21
  10. 2024ProMark: Proactive Diffusion Watermarking for Causal Attributioncited by 17
  11. 2024Language-guided Hierarchical Fine-grained Image Forgery Detection and Localizationcited by 16
  12. 2024Are CLIP features all you need for Universal Synthetic Image Origin Attribution?cited by 14
27 more
  1. 2024Synthetic Image Verification in the Era of Generative AI: What Works and What Isn't There Yetcited by 13
  2. 2024A Survey of Defenses Against AI-Generated Visual Media: Detection,Disruption, and Authenticationcited by 13
  3. 2023Open Set Synthetic Image Source Attributioncited by 12
  4. 2025Forensic Self-Descriptions Are All You Need for Zero-Shot Detection, Open-Set Source Attribution, and Clustering of AI-generated Imagescited by 11
  5. 2023What can Discriminator do? Towards Box-free Ownership Verification of Generative Adversarial Networkcited by 10
  6. 2024Detecting Origin Attribution for Text-to-Image Diffusion Modelscited by 7
  7. 2023VADER: Video Alignment Differencing and Retrievalcited by 6
  8. 2024BOSC: A Backdoor-based Framework for Open Set Synthetic Image Attributioncited by 6
  9. 2025Few-Shot Synthetic Image Attribution: Identifying Unseen Generators with Limited Samplescited by 6
  10. 2023Model Synthesis for Zero-Shot Model Attributioncited by 5
  11. 2024Are handcrafted filters helpful for attributing AI-generated images?cited by 5
  12. 2025Learning Counterfactually Decoupled Attention for Open-World Model Attributioncited by 5
  13. 2024Passive Deepfake Detection Across Multi-modalities: A Comprehensive Surveycited by 4
  14. 2024Regeneration Based Training-free Attribution of Fake Images Generated by Text-to-Image Generative Modelscited by 3
  15. 2026Attribution as Retrieval: Model-Agnostic AI-Generated Image Attributioncited by 3
  16. 2026IncreFA: Breaking the Static Wall of Generative Model Attributioncited by 3
  17. 2025Who Made This? Fake Detection and Source Attribution with Diffusion Featurescited by 2
  18. 2025Autonomous and Self-Adapting System for Synthetic Media Detection and Attributioncited by 1
  19. 2025Supervised Contrastive Learning for Few-Shot AI-Generated Image Detection and Attributioncited by 1
  20. 2025Frequency Bias Matters: Diving into Robust and Generalized Deep Image Forgery Detectioncited by 1
  21. 2026Unsupervised Synthetic Image Attribution: Alignment and Disentanglementcited by 1
  22. 2026ImageAttributionBench: How Far Are We from Generalizable Attribution?cited by 1
  23. 2023A Siamese-based Verification System for Open-set Architecture Attribution of Synthetic Imagescited by 0
  24. 2026Face-Trace: Open-Set Attribution and Progressive Discovery of Synthetic Face Generatorscited by 0
  25. 2026Representation and Reference Selection in Training-Free Synthetic Image Attributioncited by 0
  26. 2026DNA: Dual-stage Native Attribution for Generated Image Source Tracingcited by 0
  27. 2026Multi-Tool Image Editing Attribution in Facial Forgerycited by 0