Results 1 to 10 of about 12,433 (211)

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

Deepfake video detection: challenges and opportunities

Artificial Intelligence Review
Deepfake videos are a growing social issue. These videos are manipulated by artificial intelligence (AI) techniques (especially deep learning), an emerging societal issue.
Azadeh Noori Hoshyar, Feng Xia, Selena Firmin   +2 more
exaly   +2 more sources

Design and development of an efficient RLNet prediction model for deepfake video detection [PDF]

Frontiers in Big Data
IntroductionThe widespread emergence of deepfake videos presents substantial challenges to the security and authenticity of digital content, necessitating robust detection methods.
Varad Bhandarkawthekar, T. M. Navamani, Rishabh Sharma, K. Shyamala   +3 more
doaj   +2 more sources

Visual Deepfake Detection: Review of Techniques, Tools, Limitations, and Future Prospects

IEEE Access
In recent years, rapid advancements in deepfakes (incorporating Artificial Intelligence (AI), machine, and deep learning) have updated tools and techniques for manipulating multimedia. Though technology has primarily been utilized for beneficial purposes,
Naveed Ur Rehman Ahmed, Afzal Badshah, Hanan Adeel, Ayesha Tajammul, Ali Daud, Tariq Alsahfi   +5 more
doaj   +2 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

Unmasking digital deceptions: An integrative review of deepfake detection, multimedia forensics, and cybersecurity challenges. [PDF]

MethodsX
Highlights • Presents an in-depth review of deepfake generation and detection, highlighting AI methods such as GANs, face synthesis, and speech cloning.• Evaluates critically the weaknesses of biometric systems and the difficulties of cross-dataset ...
Singh S, Dhumane A.
europepmc   +2 more sources

Deepfakes

Jugend Medien Schutz-Report
Die Wirklichkeit, also das tatsächliche Gefüge der Welt und des Weltalls, ist für den Menschen nur sehr eingeschränkt erfahrbar. Die menschlichen Sinne sind begrenzt, ein Hund hört viel besser als wir und unser Auge nimmt nur bestimmte Spektren des Lichts wahr. Physisch sind wir – noch – an die Erde gebunden.
Lingala Thirupathi, Alumalla Shivani Reddy, Visnu Vardhan, Tapasvi Panchagnula, Nata Sheker Reddy Miriyala, Saritha Gattoju, T. V. Rajini Kanth   +6 more
  +14 more sources

Deepfake: definitions, performance metrics and standards, datasets, and a meta-review

Frontiers in Big Data
Recent advancements in AI, especially deep learning, have contributed to a significant increase in the creation of new realistic-looking synthetic media (video, image, and audio) and manipulation of existing media, which has led to the creation of the ...
Shujun Li, Enes Altuncu
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

DeepFake MNIST+: A DeepFake Facial Animation Dataset [PDF]

2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2021
14 ...
Jiajun Huang, Xueyu Wang, Bo Du 0001, Pei Du, Chang Xu 0002   +4 more
openaire   +2 more sources