MorDIFF: Recognition Vulnerability and Attack Detectability of Face Morphing Attacks Created by Diffusion Autoencoders-Reference-Cited by-同舟云学术

MorDIFF: Recognition Vulnerability and Attack Detectability of Face Morphing Attacks Created by Diffusion Autoencoders

Published:2023-04-19 Issue: Volume: Page:
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Container-title:2023 11th International Workshop on Biometrics and Forensics (IWBF)
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Author:

Damer Naser¹,Fang Meiling¹,Siebke Patrick¹,Kolf Jan Niklas¹,Huber Marco¹,Boutros Fadi¹

Affiliation:

1. Fraunhofer Institute for Computer Graphics Research IGD,Darmstadt,Germany

Funder

Ministry of Education

Publisher

IEEE

Link

Reference42 articles.

1. A multi-detector solution towards an accurate and generalized detection of face morphing attacks;damer;FUSION,2019

3. PW-MAD: pixel-wise supervision for generalized face morphing attack detection;damer;ISVC (1),2021

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2. Face Morphing via Adversarial Attack-based Adaptive Blending;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

3. Hierarchical Generative Network for Face Morphing Attacks;2024 IEEE 18th International Conference on Automatic Face and Gesture Recognition (FG);2024-05-27

4. Fused Classification For Differential Face Morphing Detection;2024 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW);2024-01-01

5. On the Vulnerability of Deepfake Detectors to Attacks Generated by Denoising Diffusion Models;2024 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW);2024-01-01