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The Face Deepfake Detection Challenge [PDF]

Journal of Imaging, 2022
Multimedia data manipulation and forgery has never been easier than today, thanks to the power of Artificial Intelligence (AI). AI-generated fake content, commonly called Deepfakes, have been raising new issues and concerns, but also new challenges for the research community.
Sebastiano Battiato, Giovanni Puglisi, Fabrizio Falchi   +2 more
exaly   +8 more sources

CrossDF: improving cross-domain deepfake detection with deep information decomposition [PDF]

Frontiers in Big Data
Deepfake technology represents a serious risk to safety and public confidence. While current detection approaches perform well in identifying manipulations within datasets that utilize identical deepfake methods for both training and validation, they ...
Shanmin Yang, Hui Guo, Shu Hu, Bin Zhu, Ying Fu, Siwei Lyu, Xi Wu, Xin Wang   +7 more
doaj   +2 more sources

MCW: A Generalizable Deepfake Detection Method for Few-Shot Learning [PDF]

Sensors, 2023
With the development of deepfake technology, deepfake detection has received widespread attention. Although some deepfake forensics techniques have been proposed, they are still very difficult to implement in real-world scenarios.
Lei Guan, Fan Liu, Ru Zhang, Jianyi Liu, Yifan Tang   +4 more
doaj   +2 more sources

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, Zhihua Xia, Jianwei Fei, Yujiang Lu   +3 more
doaj   +2 more sources

Analysis of Score-Level Fusion Rules for Deepfake Detection

Applied Sciences, 2022
Deepfake detection is of fundamental importance to preserve the reliability of multimedia communications. Modern deepfake detection systems are often specialized on one or more types of manipulation but are not able to generalize. On the other hand, when
Sara Concas, Simone Maurizio La Cava, Giulia Orrù, Carlo Cuccu, Jie Gao, Xiaoyi Feng, Gian Luca Marcialis, Fabio Roli   +7 more
doaj   +3 more sources

A Novel Deep Learning Approach for Deepfake Image Detection

Applied Sciences, 2022
Deepfake is utilized in synthetic media to generate fake visual and audio content based on a person’s existing media. The deepfake replaces a person’s face and voice with fake media to make it realistic-looking. Fake media content generation is unethical
Ali Raza, Kashif Munir, Mubarak Almutairi   +2 more
doaj   +3 more sources

A Survey on Speech Deepfake Detection

ACM Computing Surveys
The availability of smart devices leads to an exponential increase in multimedia content. However, advancements in deep learning have also enabled the creation of highly sophisticated Deepfake content, including speech Deepfakes, which pose a serious threat by generating realistic voices and spreading misinformation. To combat this, numerous challenges

exaly   +3 more sources

DeepFake-Adapter: Dual-Level Adapter for DeepFake Detection

International Journal of Computer Vision
IJCV 2025.
Ziwei Liu, Rui Shao, Tianxing Wu
exaly   +3 more sources

Is this real? Susceptibility to deepfakes in machines and humans [PDF]

Cognitive Research
Deepfakes are synthetic media created by deep-generative methods to fake a person’s audio-visual representation. Growing sophistication of deepfake technology poses significant challenges for both machine learning (ML) algorithms and humans. Here we used
Didem Pehlivanoglu, Mengdi Zhu, Jialong Zhen, Aude A. Gagnon-Roberge, Rebecca K. Kern, Damon Woodard, Brian S. Cahill, Natalie C. Ebner   +7 more
doaj   +2 more sources

A Robust Approach to Multimodal Deepfake Detection [PDF]

Journal of Imaging, 2023
Weiming Zhang, Honggu Liu, Stefano Tubaro   +2 more
exaly   +2 more sources