mlsanityData to 14 Oct 2026

Face Morphing Attack Generation & Detection: A Comprehensive Survey

arXiv 2011.02045 ↗First posted 3 Nov 2020cs.CV cs.CR cs.CYcited by 64

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Abstract (arXiv)

The vulnerability of Face Recognition System (FRS) to various kind of attacks (both direct and in-direct attacks) and face morphing attacks has received a great interest from the biometric community. The goal of a morphing attack is to subvert the FRS at Automatic Border Control (ABC) gates by presenting the Electronic Machine Readable Travel Document (eMRTD) or e-passport that is obtained based on the morphed face image. Since the application process for the e-passport in the majority countries requires a passport photo to be presented by the applicant, a malicious actor and the accomplice can generate the morphed face image and to obtain the e-passport. An e-passport with a morphed face images can be used by both the malicious actor and the accomplice to cross the border as the morphed face image can be verified against both of them. This can result in a significant threat as a malicious actor can cross the border without revealing the track of his/her criminal background while the details of accomplice are recorded in the log of the access control system. This survey aims to present a systematic overview of the progress made in the area of face morphing in terms of both morph generation and morph detection. In this paper, we describe and illustrate various aspects of face morphing attacks, including different techniques for generating morphed face images but also the state-of-the-art regarding Morph Attack Detection (MAD) algorithms based on a stringent taxonomy and finally the availability of public databases, which allow to benchmark new MAD algorithms in a reproducible manner. The outcomes of competitions/benchmarking, vulnerability assessments and performance evaluation metrics are also provided in a comprehensive manner. Furthermore, we discuss the open challenges and potential future works that need to be addressed in this evolving field of biometrics.

Key facts. Cited by 64 papers in the map (data through 14 Oct 2026). First posted on arXiv 3 Nov 2020.

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Citing papers per year: 2021: 7; 2022: 12; 2023: 12; 2024: 12; 2025: 15; 2026: 6.

64 papers.

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  1. 2022GAN-generated Faces Detection: A Survey and New Perspectivescited by 30
  2. 2021PW-MAD: Pixel-wise Supervision for Generalized Face Morphing Attack Detectioncited by 29
  3. 2022Synthetic Data in Human Analysis: A Surveycited by 28
  4. 2023Leveraging Diffusion For Strong and High Quality Face Morphing Attackscited by 14
  5. 2025Generalized Single-Image-Based Morphing Attack Detection Using Deep Representations from Vision Transformercited by 14
  6. 2022Analyzing Human Observer Ability in Morphing Attack Detection -- Where Do We Stand?cited by 13
  7. 2021Conditional Identity Disentanglement for Differential Face Morph Detectioncited by 12
  8. 2021Morph Detection Enhanced by Structured Group Sparsitycited by 10
  9. 2024Greedy-DiM: Greedy Algorithms for Unreasonably Effective Face Morphscited by 10
  10. 2024ONOT: a High-Quality ICAO-compliant Synthetic Mugshot Datasetcited by 10
  11. 2022On the detection of morphing attacks generated by GANscited by 9
  12. 2022Facial De-morphing: Extracting Component Faces from a Single Morphcited by 9
38 more
  1. 2024LADIMO: Face Morph Generation through Biometric Template Inversion with Latent Diffusioncited by 9
  2. 2021Single Morphing Attack Detection using Feature Selection and Visualisation based on Mutual Informationcited by 8
  3. 2022Face Morphing Attacks and Face Image Quality: The Effect of Morphing and the Unsupervised Attack Detection by Qualitycited by 8
  4. 2023Face Feature Visualisation of Single Morphing Attack Detectioncited by 8
  5. 2024Facial Demorphing via Identity Preserving Image Decompositioncited by 8
  6. 2025SelfMAD: Enhancing Generalization and Robustness in Morphing Attack Detection via Self-Supervised Learningcited by 7
  7. 2021Focused LRP: Explainable AI for Face Morphing Attack Detectioncited by 6
  8. 2022Deep Composite Face Image Attacks: Generation, Vulnerability and Detectioncited by 6
  9. 2023SDeMorph: Towards Better Facial De-morphing from Single Morphcited by 6
  10. 2024IDNet: A Novel Dataset for Identity Document Analysis and Fraud Detectioncited by 6
  11. 2024MorCode: Face Morphing Attack Generation using Generative Codebookscited by 6
  12. 2021Algorithmic Fairness in Face Morphing Attack Detectioncited by 5
  13. 20223D Face Morphing Attacks: Generation, Vulnerability and Detectioncited by 5
  14. 2022Reliable Face Morphing Attack Detection in On-The-Fly Border Control Scenario with Variation in Image Resolution and Capture Distancecited by 5
  15. 2023OTB-morph: One-Time Biometrics via Morphingcited by 5
  16. 2023Multispectral Imaging for Differential Face Morphing Attack Detection: A Preliminary Studycited by 5
  17. 2021OTB-morph: One-Time Biometrics via Morphing applied to Face Templatescited by 4
  18. 2023MorphGANFormer: Transformer-based Face Morphing and De-Morphingcited by 4
  19. 2023Towards minimizing efforts for Morphing Attacks -- Deep embeddings for morphing pair selection and improved Morphing Attack Detectioncited by 4
  20. 2024Rethinking the Vulnerabilities of Face Recognition Systems:From a Practical Perspectivecited by 4
  21. 2025Empowering Morphing Attack Detection using Interpretable Image-Text Foundation Modelcited by 4
  22. 2023Robust Face Morphing Attack Detection Using Fusion of Multiple Features and Classification Techniquescited by 3
  23. 2024SynMorph: Generating Synthetic Face Morphing Dataset with Mated Samplescited by 3
  24. 2023Differential Newborn Face Morphing Attack Detection using Wavelet Scatter Networkcited by 2
  25. 2023Voice Morphing: Two Identities in One Voicecited by 2
  26. 2024TetraLoss: Improving the Robustness of Face Recognition against Morphing Attackscited by 2
  27. 2025Metric for Evaluating Performance of Reference-Free Demorphing Methodscited by 2
  28. 2025Fragile Watermarking for Image Certification Using Deep Steganographic Embeddingcited by 2
  29. 2025FLUXSynID: A Framework for Identity-Controlled Synthetic Face Generation with Document and Live Imagescited by 2
  30. 2025Towards Zero-Shot Differential Morphing Attack Detection with Multimodal Large Language Modelscited by 2
  31. 2025StableMorph: High-Quality Face Morph Generation with Stable Diffusioncited by 2
  32. 2022Fusion-based Few-Shot Morphing Attack Detection and Fingerprintingcited by 1
  33. 2023Vulnerability of Face Morphing Attacks: A Case Study on Lookalike and Identical Twinscited by 1
  34. 2024Recent Advancement in 3D Biometrics using Monocular Cameracited by 1
  35. 20243D Face Morphing Attack Generation using Non-Rigid Registrationcited by 1
  36. 2025diffDemorph: Extending Reference-Free Demorphing to Unseen Facescited by 1
  37. 2025DOOMGAN:High-Fidelity Dynamic Identity Obfuscation Ocular Generative Morphingcited by 1
  38. 2025LoRA-Enhanced Vision Transformer for Single Image based Morphing Attack Detection via Knowledge Distillation from EfficientNetcited by 1

50 most cited of 64 All 64 (JSON)