Awesome

Awesome Comprehensive Deepfake Detection

This repository provides a comprehensive investigation of advanced single-modal and multi-modal deepfake detection elaborated in the following survey.

If you believe there are additional works that should be included in our list, please do not hesitate to send us an email (pingl@unr.edu/tao.qiqi@outlook.com/zhouty@cfar.a-star.edu.sg) or raise an issue. Your suggestions and comments are invaluable to ensuring the completeness and accuracy of our resource.

Content

• Relevant Surveys
  • Deepfake/AIGC Generation and Detection
  • Multi-modal Fact-checking
• Facial Deepfake Datasets
  • Single-modal GAN-generated Datasets
  • Single-modal Diffusion-generated Datasets
  • Multi-modal Audio-Visual Datasets
  • Multi-modal Text-Visual Datasets
• Single-modal (Visual) Deepfake Detection
  • Passive Detection
    • Naive Detection
    • Advanced Detection
      • Input Level
      • Model Level
      • Learning Level
    • Diffusion Model Detection
    • Sequential Deepfake Detection
  • Proactive Detection
    • Proactive Methods for GANs
    • Proactive Methods for Diffusion Models
• Multi-modal Deepfake Detection
  • Audio-Visual Deepfake Detection
    • Independent Learning
    • Joint Learning
      • Intermediate Fusion
      • Late Fusion
      • Multi-task Strategy
      • Regularization
    • Matching-based Learning
    • Others
  • Text-Visual Deepfake Detection
• Trustworthy Deepfake Detection
  • Adversarial Attack
  • Backdoor Attack
  • Discrepancy Minimization
  • Defense Strategies

Relevant Surveys

Deepfake/AIGC Generation and Detection

[arxiv 2024] Deepfake Generation and Detection: A Benchmark and Survey Paper Project

[arxiv 2024] Detecting Multimedia Generated by Large AI Models: A Survey Paper Project

[ECAI 2023] GAN-generated Faces Detection: A Survey and New Perspectives Paper

[NeurIPS 2023] DeepfakeBench: A Comprehensive Benchmark of Deepfake Detection Paper Project

[arxiv 2023] Deepfake detection: A comprehensive study from the reliability perspective Paper

[IJCV 2022] Countering Malicious DeepFakes: Survey, Battleground, and Horizon Paper Project

Multi-modal Fact-checking

[EMNLP 2023] Multimodal automated fact-checking: A survey Paper

Facial Deepfake Datasets

Single-modal GAN-generated Datasets

Single-modal Diffusion-generated Datasets

Multi-modal Audio-Visual Datasets

Multi-modal Text-Visual Datasets

Single-modal (Visual) Deepfake Detection

Passive Detection

Naive Detection

Visual Artifacts

1. [CVPR 2024] Rethinking the Up-Sampling Operations in CNN-based Generative Network for Generalizable Deepfake Detection Paper
2. [CVPR 2024] LAA-Net: Localized Artifact Attention Network for Quality-Agnostic and Generalizable Deepfake Detection Paper
3. [arXiv 2024] Data-Independent Operator: A Training-Free Artifact Representation Extractor for Generalizable Deepfake Detection Paper
4. [arXiv 2024] A Single Simple Patch is All You Need for AI-generated Image Detection Paper
5. [arXiv 2024] GenFace: A Large-Scale ed Face Forgery Benchmark and Cross Appearance-Edge Learning Paper
6. [TMM 2023] GLFF: Global and Local Feature Fusion for AI-synthesized Image Detection Paper
7. [CVPRW 2023] Intriguing properties of synthetic images: from generative adversarial networks to diffusion models Paper
8. [arXiv 2023] Diffusion Noise Feature: Accurate and Fast Generated Image Detection Paper
9. [CVPR 2021] Multi-attentional Deepfake Detection Paper
10. [CVPR 2020] Global Texture Enhancement for Fake Face Detection In the Wild Paper
11. [ICCV 2019] FaceForensics++: Learning to Detect Manipulated Facial Images Paper
12. [WIFS 2018] Mesonet: a compact facial video forgery detection network Paper

Consistencies-based

1. [arXiv 2024] Generalizing Deepfake Video Detection with Plug-and-Play: Video-Level Blending and Spatiotemporal Adapter Tuning Paper
2. [arXiv 2024] UniForensics: Face Forgery Detection via General Facial Representation Paper
3. [arXiv 2024] Learning Natural Representation for Face Forgery Video Detection Paper
4. [IJCV 2024] Learning Spatiotemporal Inconsistency via Thumbnail Layout for Face Deepfake Detection Paper
5. [CVPR 2024] Exploiting Style Latent Flows for Generalizing Deepfake Video Detection Paper
6. [arxiv 2024] Compressed Deepfake Video Detection Based on 3D Spatiotemporal Trajectories Paper
7. [AAAI 2023] Noise based deepfake detection via multi-head relative-interaction Paper
8. [ICCV 2023] TALL: Thumbnail Layout for Deepfake Video Detection Paper
9. [CVPR 2023] AltFreezing for More General Video Face Forgery Detection Paper
10. [TCSVT 2023] MRE-Net: Multi-Rate Excitation Network for Deepfake Video Detection Paper
11. [WACV 2023] TI2Net: Temporal Identity Inconsistency Network for Deepfake Detection Paper
12. [ACM MM Asia 2022] Latent pattern sensing: Deepfake video detection via predictive representation learning Paper
13. [CVPR 2021] Lips don’t lie: A generalisable and robust approach to face forgery detection Paper
14. [ICCV 2021] Exploring Temporal Coherence for More General Video Face Forgery Detection Paper
15. [ACM MM 2020] DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms Paper
16. [WIFS 2018] In Ictu Oculi: Exposing AI Created Fake Videos by Detecting Eye Blinking Paper

Advanced Detection

Input Level

Data Augmentation

1. [arXiv 2024] Can We Leave Deepfake Data Behind in Training Deepfake Detector? Paper
2. [arXiv 2024] ED4: Explicit Data-level Debiasing for Deepfake Detection Paper
3. [arXiv 2024] FSBI: Deepfakes Detection with Frequency Enhanced Self-Blended Images Paper
4. [arXiv 2024] FreqBlender: Enhancing DeepFake Detection by Blending Frequency Knowledge Paper
5. [ICCV 2023] SeeABLE: Soft Discrepancies and Bounded Contrastive Learning for Exposing Deepfakes Paper
6. [arXiv 2023] Transcending Forgery Specificity with Latent Space Augmentation for Generalizable Deepfake Detection Paper
7. [CVPR 2022] Detecting Deepfakes with Self-Blended Images Paper
8. [CVPR 2022] Self-supervised Learning of Adversarial Example: Towards Good Generalizations for Deepfake Detection Paper
9. [CVPR 2021] Representative Forgery Mining for Fake Face Detecti Paper
10. [ICCV 2021] Learning Self-Consistency for Deepfake Detection Paper

Frequency-space Based

1. [arXiv 2024] Multiple Contexts and Frequencies Aggregation Network for Deepfake Detection Paper
2. [AAAI 2024] Frequency-Aware Deepfake Detection: Improving Generalizability through Frequency Space Learning Paper
3. [ICASSP 2024] Frequency Masking for Universal Deepfake Detection Paper
4. [CVPR 2023] Dynamic Graph Learning with Content-guided Spatial-Frequency Relation Reasoning for Deepfake Detection Paper
5. [AAAI 2022] FrePGAN: Robust Deepfake Detection Using Frequency-level Perturbations Paper
6. [AAAI 2022] ADD: Frequency Attention and Multi-View based Knowledge Distillation to Detect Low-Quality Compressed Deepfake Images Paper
7. [CVPR 2021] Spatial-Phase Shallow Learning: Rethinking Face Forgery Detection in Frequency Domain Paper
8. [CVPR 2021] Generalizing Face Forgery Detection with High-frequency Features Paper
9. [CVPR 2021] Frequency-aware Discriminative Feature Learning Supervised by Single-Center Loss for Face Forgery Detection Paper
10. [AAAI 2021] Local Relation Learning for Face Forgery Detection Paper
11. [ECCV 2020] Thinking in Frequency: Face Forgery Detection by Mining Frequency-aware Clues Paper

Model Level

Transformer-based

1. [arXiv 2024] Standing on the Shoulders of Giants: Reprogramming Visual-Language Model for General Deepfake Detection Paper
2. [arXiv 2024] Guided and Fused: Efficient Frozen CLIP-ViT with Feature Guidance and Multi-Stage Feature Fusion for Generalizable Deepfake Detection Paper
3. [arXiv 2024] Open-Set Deepfake Detection: A Parameter-Efficient Adaptation Method with Forgery Style Mixture Paper
4. [arXiv 2024] A Timely Survey on Vision Transformer for Deepfake Detection Paper
5. [arXiv 2024] Exploring Self-Supervised Vision Transformers for Deepfake Detection: A Comparative Analysis Paper
6. [arXiv 2024] Mixture of Low-rank Experts for Transferable AI-Generated Image Detection Paper
7. [arXiv 2024] MoE-FFD: Mixture of Experts for Generalized and Parameter-Efficient Face Forgery Detection Paper
8. [CVPR 2023] AUNet: Learning Relations Between Action Units for Face Forgery Detection Paper
9. [ACM MM 2023] UMMAFormer: A Universal Multimodal-adaptive Transformer Framework for Temporal Forgery Localization Paper
10. [ICCVW 2023] Undercover Deepfakes: Detecting Fake Segments in Video Paper
11. [arXiv 2023] DeepFake-Adapter: Dual-Level Adapter for DeepFake Detection Paper
12. [MIPR 2023] Enhancing General Face Forgery Detection via Vision Transformer with Low-Rank Adaptation Paper

VLM-based

1. [WACV 2025] DeCLIP: Decoding CLIP representations for deepfake localization Paper
2. [arXiv 2024] MFCLIP: Multi-modal Fine-grained CLIP for Generalizable Diffusion Face Forgery Detection Paper
3. [arXiv 2024] FFAA: Multimodal Large Language Model based Explainable Open-World Face Forgery Analysis Assistant Paper
4. [arXiv 2024] C2P-CLIP: Injecting Category Common Prompt in CLIP to Enhance Generalization in Deepfake Detection Paper
5. [arXiv 2024] GM-DF: Generalized Multi-Scenario Deepfake Detection Paper
6. [arXiv 2024] Towards More General Video-based Deepfake Detection through Facial Feature Guided Adaptation for Foundation Model Paper
7. [arXiv 2024] FakeBench: Uncover the Achilles' Heels of Fake Images with Large Multimodal Models Paper
8. [CVPR Workshop 2024] Can ChatGPT Detect DeepFakes? A Study of Using Multimodal Large Language Models for Media Forensics Paper
9. [arXiv 2024] SHIELD: An Evaluation Benchmark for Face Spoofing and Forgery Detection with Multimodal Large Language Models Paper
10. [arXiv 2024] Common Sense Reasoning for Deep Fake Detection Paper
11. [ACM ICMRW 2024] Towards Quantitative Evaluation of Explainable AI Methods for Deepfake Detection Paper
12. [arxiv 2023] Forgery-aware Adaptive Vision Transformer for Face Forgery Detection Paper
13. [arXiv 2023] Towards General Visual-Linguistic Face Forgery Detection Paper

Learning Level

Advanced Loss

1. [ToMM 2024] Domain-invariant and Patch-discriminative Feature Learning for General Deepfake Detection Paper
2. [ICME 2023] Domain-Invariant Feature Learning for General Face Forgery Detection Paper
3. [ICDM 2023] Concentric Ring Loss for Face Forgery Detection Paper

Disentangled Representation

1. [CVPR 2024] Preserving Fairness Generalization in Deepfake Detection Paper
2. [arXiv 2024] Decoupling Forgery Semantics for Generalizable Deepfake Detection Paper
3. [arXiv 2023] Improving Cross-dataset Deepfake Detection with Deep Information Decomposition Paper
4. [ICCV 2023] UCF: Uncovering Common Features for Generalizable Deepfake Detection Paper
5. [ECCV 2022] Exploring Disentangled Content Information for Face Forgery Detection Paper

Reconstruction

1. [CVPR 2023] MARLIN: Masked Autoencoder for facial video Representation LearnINg Paper
2. [CVPR 2022] End-to-End Reconstruction-Classification Learning for Face Forgery Detection Paper
3. [IJCAI 2021] Beyond the Spectrum: Detecting Deepfakes via Re-Synthesis Paper
4. [CVPRW 2020] OC-FakeDect: Classifying Deepfakes Using One-class Variational Autoencoder Paper

Manipulation Localization

1. [CVPR 2024] EditGuard: Versatile Image Watermarking for Tamper Localization and Copyright Protection Paper
2. [WACV 2024] Weakly-supervised deepfake localization in diffusion-generated images Paper
3. [arXiv 2024] Delocate: Detection and Localization for Deepfake Videos with Randomly-Located Tampered Traces Paper
4. [CVPR 2023] MaLP: Manipulation Localization Using a Proactive Scheme Paper
5. [CVPR 2023] Implicit Identity Leakage: The Stumbling Block to Improving Deepfake Detection Generalization Paper
6. [ACM MM 2023] Locate and Verify: A Two-Stream Network for Improved Deepfake Detection Paper
7. [CVPR 2020] Face X-ray for More General Face Forgery Detection Paper
8. [CVPR 2020] On the Detection of Digital Face Manipulation Paper

Identity Discrepancy

1. [CVPR 2023] Implicit Identity Driven Deepfake Face Swapping Detection Paper
2. [CVPR 2022] Protecting Celebrities from DeepFake with Identity Consistency Transformer Paper
3. [TPAMI 2021] DeepFake Detection Based on Discrepancies Between Faces and Their Context Paper
4. [ICCV 2021] ID-Reveal: Identity-aware DeepFake Video Detection Paper

Knowledge Distillation

1. [arXiv 2023] DomainForensics: Exposing Face Forgery across Domains via Bi-directional Adaptation Paper
2. [AAAI 2022] ADD: Frequency Attention and Multi-View based Knowledge Distillation to Detect Low-Quality Compressed Deepfake Images Paper
3. [ACM MM 2021] CoReD: Generalizing Fake Media Detection with Continual Representation using Distillation Paper
4. [CVPRW 2021] FReTAL: Generalizing Deepfake Detection using Knowledge Distillation and Representation Learning Paper
5. [Journal of Mathematical Imaging and Vision 2015] Sliced and Radon Wasserstein Barycenters of Measures Paper

Fine-grained Prediction

1. [arXiv 2024] Semantics-Oriented Multitask Learning for DeepFake Detection: A Joint Embedding Approach Paper
2. [ToMM 2024] Mastering Deepfake Detection: A Cutting-Edge Approach to Distinguish GAN and Diffusion-Model Images Paper
3. [CVPR 2023] Hierarchical Fine-Grained Image Forgery Detection and Localization Paper
4. [ICCV 2023] Controllable Guide-Space for Generalizable Face Forgery Detection Paper

Diffusion Model Detection

1. [CVPR 2024] LaRE^2: Latent Reconstruction Error Based Method for Diffusion-Generated Image Detection Paper
2. [VISAPP 2024] Towards the Detection of Diffusion Model Deepfakes Paper
3. [arXiv 2024] Diffusion Facial Forgery Detection Paper
4. [ICCV 2023] DIRE for Diffusion-Generated Image Detection Paper
5. [ICASSP 2023] On the detection of synthetic images generated by diffusion models Paper
6. [ICCVW 2023] Detecting Images Generated by Deep Diffusion Models using their Local Intrinsic Dimensionality Paper
7. [ICMLW 2023] Exposing the Fake: Effective Diffusion-Generated Images Detection Paper

Sequential Deepfake Detection

1. [ECCV 2022] Detecting and Recovering Sequential DeepFake Manipulation Paper
2. [arXiv 2023] Robust Sequential DeepFake Detection Paper
3. [CVPR 2024] Contrastive Learning for DeepFake Classification and Localization via Multi-Label Ranking Paper
4. [TIFS 2024] Multi-Collaboration and Multi-Supervision Network for Sequential Deepfake Detection Resources Paper
5. [Transactions on Consumer Electronics 2024] Detecting Sequential Deepfake Manipulation via Spectral With Pyramid Attention in Consumer IoT Paper

Proactive Detection

Proactive Methods for GANs

1. [IJCAI 2024] Are Watermarks Bugs for Deepfake Detectors? Rethinking Proactive Forensics Paper
2. [TIFS 2024] Dual Defense: Adversarial, Traceable, and Invisible Robust Watermarking against Face Swapping Paper
3. [CVPR 2023] MaLP: Manipulation Localization Using a Proactive Scheme Paper
4. [ACM MM 2023] SepMark: Deep Separable Watermarking for Unified Source Tracing and Deepfake Detection Paper
5. [arXiv 2023] Feature Extraction Matters More: Universal Deepfake Disruption through Attacking Ensemble Feature Extractors Paper
6. [arXiv 2023] Robust Identity Perceptual Watermark Against Deepfake Face Swapping Paper
7. [CVPR 2022] Proactive Image Manipulation Detection Paper
8. [ICLR 2022] Responsible Disclosure of Generative Models Using Scalable Fingerprinting Paper
9. [ECCV 2022] TAFIM: Targeted Adversarial Attacks against Facial Image Manipulations Paper
10. [AAAI 2022] CMUA-Watermark: A Cross-Model Universal Adversarial Watermark for Combating Deepfake Paper
11. [IJCAI 2022] Anti-Forgery: Towards a Stealthy and Robust DeepFake Disruption Attack via Adversarial Perceptual-aware Perturbations Paper
12. [AAAI 2021] Initiative Defense against Facial Manipulation Paper
13. [CVPRW 2020] Disrupting Deepfakes: Adversarial Attacks Against Conditional Image Translation Networks and Facial Manipulation Systems Paper
14. [WACVW 2020] Disrupting Image-Translation-Based DeepFake Algorithms with Adversarial Attacks Paper

Proactive Methods for Diffusion Models

1. [ICLR 2024] DIAGNOSIS: Detecting Unauthorized Data Usages in Text-to-image Diffusion Models Paper
2. [NeurIPSW 2024] DiffusionShield: A Watermark for Data Copyright Protection against Generative Diffusion Models Paper
3. [ICCV 2023] The Stable Signature: Rooting Watermarks in Latent Diffusion Models Paper
4. [TPS-ISA 2023] Invisible Watermarking for Audio Generation Diffusion Models Paper
5. [arXiv 2023] A Recipe for Watermarking Diffusion Models Paper
6. [arXiv 2023] LEAT: Towards Robust Deepfake Disruption in Real-World Scenarios via Latent Ensemble Attack Paper

Multi-modal Deepfake Detection

Audio-Visual Deepfake Detection

Independent Learning

1. [Applied Soft Computing 2023] AVFakeNet: A unified end-to-end Dense Swin deep learning model for audio–visual​ deepfakes detection Paper
2. [APSIPA ASC 2022] Multimodal Forgery Detection Using Ensemble Learning Paper
3. [ICCV 2021] Joint Audio-Visual Deepfake Detection Paper
4. [ACM MMW 2021] Evaluation of an Audio-Video Multimodal Deepfake Dataset using Unimodal and Multimodal Detectors Paper

Joint Learning

Intermediate Fusion

Cross-Attention

1. [BMVC 2024] Detecting Audio-Visual Deepfakes with Fine-Grained Inconsistencies Paper
2. [arXiv 2024] Contextual Cross-Modal Attention for Audio-Visual Deepfake Detection and Localization Paper
3. [TIFS 2023] AVoiD-DF: Audio-Visual Joint Learning for Detecting Deepfake Paper
4. [arXiv 2022] An Audio-Visual Attention Based Multimodal Network for Fake Talking Face Videos Detection Paper
5. [ICCV 2021] Joint Audio-Visual Deepfake Detection Paper

Late Fusion

Concatenation & Addition

1. [arXiv 2024] Integrating Audio-Visual Features for Multimodal Deepfake Detection Paper
2. [arXiv 2024] AVT2-DWF: Improving Deepfake Detection with Audio-Visual Fusion and Dynamic Weighting Strategies Paper
3. [Image Communication 2023] Magnifying multimodal forgery clues for Deepfake detection Paper
4. [arXiv 2023] DF-TransFusion: Multimodal Deepfake Detection via Lip-Audio Cross-Attention and Facial Self-Attention Paper
5. [DICTA 2022] Do You Really Mean That? Content Driven Audio-Visual Deepfake Dataset and Multimodal Method for Temporal Forgery Localization Paper
6. [APSIPA ASC 2022] Multimodal Forgery Detection Using Ensemble Learning Paper
7. [ACM MMW 2021] Evaluation of an Audio-Video Multimodal Deepfake Dataset using Unimodal and Multimodal Detectors Paper

Attention

1. [ICASSP 2024] Cross-Modality and Within-Modality Regularization for Audio-Visual DeepFake Detection Paper
2. [arXiv 2024] AVT2-DWF: Improving Deepfake Detection with Audio-Visual Fusion and Dynamic Weighting Strategies Paper
3. [arXiv 2023] MIS-AVoiDD: Modality Invariant and Specific Representation for Audio-Visual Deepfake Detection Paper

MLP Mixer Layer

1. [CVPRW 2023] Multimodaltrace: Deepfake Detection using Audiovisual Representation Learning Paper

Multi-task Strategy

1. [ICME 2024] Explicit Correlation Learning for Generalizable Cross-Modal Deepfake Detection Paper
2. [TIFS 2023] AVoiD-DF: Audio-Visual Joint Learning for Detecting Deepfake Paper
3. [CVPRW 2023] Multimodaltrace: Deepfake Detection using Audiovisual Representation Learning Paper
4. [arXiv 2024] Integrating Audio-Visual Features for Multimodal Deepfake Detection Paper
5. [ICCV 2021] Joint Audio-Visual Deepfake Detection Paper

Regularization

1. [ICASSP 2024] Cross-Modality and Within-Modality Regularization for Audio-Visual DeepFake Detection Paper
2. [TIFS 2023] AVoiD-DF: Audio-Visual Joint Learning for Detecting Deepfake Paper
3. [Image Communication 2023] Magnifying multimodal forgery clues for Deepfake detection Paper
4. [arXiv 2023] MIS-AVoiDD: Modality Invariant and Specific Representation for Audio-Visual Deepfake Detection Paper

Matching-based Learning

1. [ICIP 2024] Statistics-aware Audio-visual Deepfake Detector Paper
2. [ToMM 2023] Voice-Face Homogeneity Tells Deepfake Paper
3. [arXiv 2023] Unsupervised Multimodal Deepfake Detection Using Intra- and Cross-Modal Inconsistencies Paper

Others

1. [CVPR 2024] AVFF: Audio-Visual Feature Fusion for Video Deepfake Detection Paper
2. [CVPR 2023] Self-Supervised Video Forensics by Audio-Visual Anomaly Detection Paper
3. [ToMM 2023] Multimodal Neurosymbolic Approach for Explainable Deepfake Detection Paper
4. [TCSVT 2023] PVASS-MDD: Predictive Visual-audio Alignment Self-supervision for Multimodal Deepfake Detection Paper
5. [CVPRW 2023] Audio-Visual Person-of-Interest DeepFake Detection Paper

Visual-Text Deepfake Detection

1. [TPAMI 2024] Detecting and Grounding Multi-Modal Media Manipulation and Beyond Paper
2. [ICASSP 2024] Exploiting Modality-Specific Features For Multi-Modal Manipulation Detection And Grounding Paper
3. [ICME 2024] Counterfactual Explanations for Face Forgery Detection via Adversarial Removal of Artifacts Paper
4. [arXiv 2023] Unified Frequency-Assisted Framework for Detecting and Grounding Multi-Modal Manipulation Paper
5. [CVPR 2023] Detecting and Grounding Multi-Modal Media Manipulation Paper

Challenge

1. [ACM MM 2024] 1M-Deepfakes Detection Challenge Paper

Trustworthy Deepfake Detection

Adversarial Attack

1. [AAAI 2024] TraceEvader: Making DeepFakes More Untraceable via Evading the Forgery Model Attribution Paper
2. [ICASSP 2024] AdvShadow: Evading DeepFake Detection via Adversarial Shadow Attack Paper
3. [CVPR 2023] Evading Forensic Classifiers with Attribute-Conditioned Adversarial Faces Paper
4. [ICCV 2023] Frequency-aware GAN for Adversarial Manipulation Generation Paper
5. [TCSVT 2023] Dodging DeepFake Detection via Implicit Spatial-Domain Notch Filtering Paper
6. [arXiv 2023] Exploring Decision-based Black-box Attacks on Face Forgery Detection Paper
7. [arXiv 2023] Exploring Decision-based Black-box Attacks on Face Forgery Detection Paper
8. [arXiv 2023] AVA: Inconspicuous Attribute Variation-based Adversarial Attack bypassing DeepFake Detection Paper
9. [arXiv 2023] Turn Fake into Real: Adversarial Head Turn Attacks Against Deepfake Detection Paper
10. [CVPR 2022] Exploring Frequency Adversarial Attacks for Face Forgery Detection Paper
11. [WDCW 2022] Evaluating Robustness of Sequence-based Deepfake Detector Models by Adversarial Perturbation Paper
12. [ICIP 2021] Imperceptible Adversarial Examples for Fake Image Detection Paper
13. [CVPRW2021] Adversarial Threats to DeepFake Detection: A Practical Perspective Paper
14. [WACV 2021] Adversarial Deepfakes: Evaluating Vulnerability of Deepfake Detectors to Adversarial Examples Paper
15. [CVPRW 2020] Evading Deepfake-Image Detectors with White- and Black-Box Attacks Paper
16. [ECCVW 2020] Adversarial Attack on Deepfake Detection Using RL Based Texture Patches Paper
17. [IJCNN 2020] Adversarial Perturbations Fool Deepfake Detectors Paper

Backdoor Attack

1. [ICLR 2024] Poisoned Forgery Face: Towards Backdoor Attacks on Face Forgery Detection Paper
2. [arXiv 2024] Is It Possible to Backdoor Face Forgery Detection with Natural Triggers? Paper
3. [BigDIA 2023] Real is not True: Backdoor Attacks Against Deepfake Detection Paper

Discrepancy Minimization

1. [AAAI 2024] Spectrum Translation for Refinement of Image Generation (STIG) Based on Contrastive Learning and Spectral Filter Profile Paper
2. [WACVW 2024] On the Vulnerability of DeepFake Detectors to Attacks Generated by Denoising Diffusion Models Paper
3. [CVPR 2023] Evading DeepFake Detectors via Adversarial Statistical Consistency Paper
4. [IEEE Transactions on Dependable and Secure Computing 2023] Making DeepFakes More Spurious: Evading Deep Face Forgery Detection via Trace Removal Attack Paper
5. [CVPR 2022] Think Twice Before Detecting GAN-generated Fake Images from their Spectral Domain Imprints Paper
6. [ACM MM 2022] Defeating DeepFakes via Adversarial Visual Reconstruction Paper
7. [CVPR 2021] Exploring Adversarial Fake Images on Face Manifold Paper
8. [ACM MM 2020] FakePolisher: Making DeepFakes More Detection-Evasive by Shallow Reconstruction Paper
9. [arXiv 2020] FakeRetouch: Evading DeepFakes Detection via the Guidance of Deliberate Noise Paper

Defense Strategies

1. [WACV 2024] D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint Ensembles Paper
2. [TIFS 2024] DF-RAP: A Robust Adversarial Perturbation for Defending Against Deepfakes in Real-World Social Network Scenarios Paper
3. [ICMM 2024] Adversarially Robust Deepfake Detection via Adversarial Feature Similarity Learning Paper
4. [arXiv 2024] XAI-Based Detection of Adversarial Attacks on Deepfake Detectors Paper
5. [FG 2023] FaceGuard: A Self-Supervised Defense Against Adversarial Face Images Paper
6. [IEEE Symposium Series on Computational Intelligence 2022] Adversarially Robust Deepfake Video Detection Paper
7. [Journal of Electronic Imaging 2021] EnsembleDet: ensembling against adversarial attack on deepfake detection Paper
8. [arXiv 2021] Adversarially robust deepfake media detection using fused convolutional neural network predictions Paper

Efficient Deepfake Detection

1. [arXiv 2024] Real-Time Deepfake Detection in the Real-World Paper
2. [CVPR 2024 DFAD Workshop] Faster than lies: Real-time deepfake detection using binary neural networks Paper

Privacy-aware Deepfake Detection

1. [arXiv 2024] Federated Face Forgery Detection Learning with Personalized Representation Paper
2. [TIFS 2023] FedForgery: generalized face forgery detection with residual federated learning Paper
3. [2022 IEEE 24th International Workshop on Multimedia Signal Processing (MMSP)] Deepfake Detection with Data Privacy Protection Paper