Results 111 to 120 of about 6,295 (185)

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

A Robust Approach to Multimodal Deepfake Detection. [PDF]

J Imaging, 2023
Salvi D, Liu H, Mandelli S, Bestagini P, Zhou W, Zhang W, Tubaro S.   +6 more
europepmc   +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

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

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

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  

Deepfake Detection Using XceptionNet

International Journal of Scientific Research in Science and Technology
The rapid rise of synthetic media, especially deepfakes, has sparked major concerns around misinformation, identity fraud, and diminishing public confidence in visual content. As these altered videos grow increasingly realistic, there is a pressing demand for reliable and scalable detection methods.
null Muskan Kumari, null Sanya Gupta, null Neha Singh   +2 more
openaire   +1 more source

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