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A Survey on Deepfake Video Detection [PDF]
IET Biometrics, 2021 Recently, deepfake videos, generated by deep learning algorithms, have attracted widespread attention. Deepfake technology can be used to perform face manipulation with high realism.
Peipeng Yu +3 more
doaj +2 more sources
Improving Fairness in Deepfake Detection
2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023 Despite the development of effective deepfake detection models in recent years, several recent studies have demonstrated that biases in the training data utilized to develop deepfake detection models can lead to unfair performance for demographic groups ...
Chen, George H. +4 more
core +2 more sources
Robust Sequential DeepFake Detection
International Journal of Computer Vision, 2023 Since photorealistic faces can be readily generated by facial manipulation technologies nowadays, potential malicious abuse of these technologies has drawn great concerns. Numerous deepfake detection methods are thus proposed.
Liu, Ziwei, Shao, Rui, Wu, Tianxing
core +2 more sources
Audio Deepfake Detection: A Survey
CoRR, 2023 Audio deepfake detection is an emerging active topic. A growing number of literatures have aimed to study deepfake detection algorithms and achieved effective performance, the problem of which is far from being solved.
Tao, Jianhua +5 more
core +2 more sources
The Creation and Detection of Deepfakes [PDF]
ACM Computing Surveys, 2021 Generative deep learning algorithms have progressed to a point where it is difficult to tell the difference between what is real and what is fake. In 2018, it was discovered how easy it is to use this technology for unethical and malicious applications, such as the spread of misinformation, impersonation of political leaders, and the defamation of ...
Yisroel Mirsky, Wenke Lee
openaire +2 more sources
DeepFake-o-meter: An Open Platform for DeepFake Detection [PDF]
CoRR, 2021 In recent years, the advent of deep learning-based techniques and the significant reduction in the cost of computation resulted in the feasibility of creating realistic videos of human faces, commonly known as DeepFakes. The availability of open-source tools to create DeepFakes poses as a threat to the trustworthiness of the online media. In this work,
Yuezun Li +4 more
openaire +3 more sources
Multi-attentional Deepfake Detection [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 CVPR2021 ...
Hanqing Zhao +5 more
openaire +2 more sources
The detection of political deepfakes
Journal of Computer-Mediated Communication, 2022 AbstractDeepfake technology, allowing manipulations of audiovisual content by means of artificial intelligence, is on the rise. This has sparked concerns about a weaponization of manipulated videos for malicious ends. A theory on deepfake detection is presented and three preregistered studies examined the detection of deepfakes in the political realm ...
Markus Appel, Fabian Prietzel
openaire +1 more source
ClueCatcher: Catching Domain-Wise Independent Clues for Deepfake Detection
Mathematics, 2023 Deepfake detection is a focus of extensive research to combat the proliferation of manipulated media. Existing approaches suffer from limited generalizability and struggle to detect deepfakes created using unseen techniques.
Eun-Gi Lee, Isack Lee, Seok-Bong Yoo
doaj +1 more source
Proceedings of the 1st Workshop on Security Implications of Deepfakes and Cheapfakes, 2022 AbstractOne particular disconcerting form of disinformation are the impersonating audios/videos backed by advanced AI technologies, in particular, deep neural networks (DNNs). These media forgeries are commonly known as the DeepFakes. The AI-based tools are making it easier and faster than ever to create compelling fakes that are challenging to spot ...
+5 more sources