Results 111 to 120 of about 6,210 (184)

AI-Powered Deepfake Detection

International Research Journal on Advanced Engineering Hub (IRJAEH)
This research work presents a method that utilizes minimal training data and time to generate customized, photo- realistic talking head models. The technique employs few-shot learning, enabling the generation of satisfactory results from a single image, with improved fidelity using additional inputs.
null Sahana Sunkad, null Dr. Sridevi Malipatil   +1 more
openaire   +1 more source

Generative Artificial Intelligence and the Evolving Challenge of Deepfake Detection: A Systematic Analysis

Journal of Sensor and Actuator Networks
Deepfake technology, which employs advanced generative artificial intelligence to create hyper-realistic synthetic media, poses significant challenges across various sectors, including security, entertainment, and education.
Reza Babaei, Samuel Cheng, Rui Duan, Shangqing Zhao   +3 more
doaj   +1 more source

FakeSound: Deepfake General Audio Detection

With the advancement of audio generation, generative models can produce highly realistic audios. However, the proliferation of deepfake general audio can pose negative consequences.
Li, Baihan, Liang, Zheng, Wu, Mengyue, Xie, Zeyu, Xu, Xuenan, Yu, Kai   +5 more
core  

Multimodal Deepfake Detection Frameworks:Survey

INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Abstract—The rapid advancement of deepfake technology poses significant threats to information authenticity, identity protection, and societal trust. This paper presents a survey of multimodal deepfake detection frameworks with a particular emphasis on combining Efficient Temporal Modeling for Classification (ETMC) in video analysis and RawNet-based ...
Inchara Poovaiah A, Chakrapani D S, Akshata T Rathod, Aqsah Sehreen, Dhanalakshmi S   +4 more
openaire   +1 more source

Multiclass AI-Generated Deepfake Face Detection Using Patch-Wise Deep Learning Model

Computers
In response to the rapid advancements in facial manipulation technologies, particularly facilitated by Generative Adversarial Networks (GANs) and Stable Diffusion-based methods, this paper explores the critical issue of deepfake content creation.
Muhammad Asad Arshed, Shahzad Mumtaz, Muhammad Ibrahim, Christine Dewi, Muhammad Tanveer, Saeed Ahmed   +5 more
doaj   +1 more source

On the Generalization of Deep Learning Models in Video Deepfake Detection. [PDF]

J Imaging, 2023
Coccomini DA, Caldelli R, Falchi F, Gennaro C.   +3 more
europepmc   +1 more source

Detecting Musical Deepfakes

The proliferation of Text-to-Music (TTM) platforms has democratized music creation, enabling users to effortlessly generate high-quality compositions. However, this innovation also presents new challenges to musicians and the broader music industry.
openaire   +2 more sources

Deepfake Video Traceability and Authentication via Source Attribution

IET Biometrics
In recent years, deepfake videos have emerged as a significant threat to societal and cybersecurity landscapes. Artificial intelligence (AI) techniques are used to create convincing deepfakes. The main counter method is deepfake detection.
Canghai Shi, Minglei Qiao, Zhuang Li, Zahid Akhtar, Bin Wang, Meng Han, Tong Qiao   +6 more
doaj   +1 more source

PUDD: Towards Robust Multi-modal Prototype-based Deepfake Detection

Deepfake techniques generate highly realistic data, making it challenging for humans to discern between actual and artificially generated images. Recent advancements in deep learning-based deepfake detection methods, particularly with diffusion models ...
Angelov, Plamen, Li, Yi, Pellcier, Alvaro Lopez   +2 more
core  

Local attention and long-distance interaction of rPPG for deepfake detection. [PDF]

Vis Comput, 2023
Wu J, Zhu Y, Jiang X, Liu Y, Lin J.
europepmc   +1 more source