Detecting DeepFake, FaceSwap and Face2Face facial forgeries using frequency CNN
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-020-10420-8.pdf
Reference32 articles.
1. Afchar D, Nozick V, Yamagishi J, Echizen I (2018) Mesonet: a compact facial video forgery detection network. In: 2018 IEEE International workshop on information forensics and security (WIFS), pp 1–7
2. Baek J, Yoo Y, Bae S (2020) Generative adversarial ensemble learning for face forensics. IEEE Access 8:45421–45431
3. Bayar B, Stamm M (2016) A deep learning approach to universal image manipulation detection using a new convolutional layer. pp 5–10. https://doi.org/10.1145/2909827.2930786
4. Bianco S, Cadene R, Celona L, Napoletano P (2018) Benchmark analysis of representative deep neural network architectures. IEEE Access 6:64270–64277
5. Cozzolino D, Poggi G, Verdoliva L (2017) Recasting residual-based local descriptors as convolutional neural networks: an application to image forgery detection. In: Proceedings of the 5th ACM workshop on information hiding and multimedia security, IH&MMSec ’17, pp 159–164, Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3082031.3083247
Cited by 38 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. SFormer: An end-to-end spatio-temporal transformer architecture for deepfake detection;Forensic Science International: Digital Investigation;2024-12
2. Cyber Security Focused Deepfake Detection System Using Big Data;SN Computer Science;2024-08-01
3. AmazingFS: A High-Fidelity and Occlusion-Resistant Video Face-Swapping Framework;Electronics;2024-07-29
4. Deepfake video detection: challenges and opportunities;Artificial Intelligence Review;2024-05-29
5. Detecting Deepfake Images: A Deep Learning Approach with Streamlit Integration;2024 International Conference on Science Technology Engineering and Management (ICSTEM);2024-04-26
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3