Results 11 to 20 of about 2,785,599 (172)

Multi-label Deepfake Classification [PDF]

, 2023
peer reviewedIn this paper, we investigate the suitability of current multi-label classification approaches for deepfake detection. With the recent advances in generative modeling, new deepfake detection methods have been proposed.
NGUYEN, van Dat, Ghorbel, Enjie, AOUADA, Djamila, SINGH, Inder Pal, MEJRI, Nesryne   +4 more
core   +1 more source

UNTAG: Learning Generic Features for Unsupervised Type-Agnostic Deepfake Detection [PDF]

, 2023
peer reviewedThis paper introduces a novel framework for unsupervised type-agnostic deepfake detection called UNTAG. Existing methods are generally trained in a supervised manner at the classification level, focusing on detecting at most two types of ...
GHORBEL, Enjie, AOUADA, Djamila, MEJRI, Nesryne   +2 more
core   +1 more source

FDS_2D: rethinking magnitude-phase features for DeepFake detection

, 2023
To reduce the harm of forged information, more and more detection methods use frequency domain information. They mostly take spectra as clues to identify fake content. However, the current work tends to use only one of the magnitude and phase spectra for
Fang, Xianjin, Yang, Gaoming, Zhang, Ji, Wei, Anxing, Gaoming Yang, Anxing Wei, Xianjin Fang, Ji Zhang   +7 more
core   +1 more source

A Survey on Deepfake Video Detection

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   +1 more source

Human Perception of Audio Deepfakes [PDF]

, 2022
The recent emergence of deepfakes has brought manipulated and generated content to the forefront of machine learning research. Automatic detection of deepfakes has seen many new machine learning techniques, however, human detection capabilities are far ...
Müller, Nicolas M., Müller, Nicholas M., Pizzi, Karla, Williams, Jennifer, Müller, Nicolas   +4 more
core   +1 more source

Detection of Frauds in Deep Fake Using Deep Learning

Engineering Proceedings
Research on DeepFake detection using deep neural networks (DNNs) has gained more attention in an effort to detect and categorize DeepFakes. In essence, DeepFakes are regenerated content made by changing particular DNN model elements.
Osipilli Aparna, Pakanati Rani, Tulluri Ramya, Tanneru Priyanka, Neela Sundari, P. G. K. Sirisha, Repudi Ramesh, Dama Anand   +7 more
doaj   +1 more source

Improving Fairness in Deepfake Detection [PDF]

, 2023
Despite the development of effective deepfake detectors in recent years, recent studies have demonstrated that biases in the data used to train these detectors can lead to disparities in detection accuracy across different races and genders.
Chen, George H., Lyu, Siwei, Ju, Yan, Jia, Shan, Hu, Shu   +4 more
core   +1 more source

Improving Video Vision Transformer for Deepfake Video Detection Using Facial Landmark, Depthwise Separable Convolution and Self Attention

IEEE Access
In this paper, we present our result of research in video deepfake detection. We built a deepfake detection system to detect whether a video is a deepfake or real. The deepfake detection algorithm still struggle in providing a sufficient accuracy values,
Kurniawan Nur Ramadhani, Rinaldi Munir, Nugraha Priya Utama   +2 more
doaj   +1 more source

Deepfake forensics: a survey of digital forensic methods for multimodal deepfake identification on social media [PDF]

PeerJ Computer Science
The rapid advancement of deepfake technology poses an escalating threat of misinformation and fraud enabled by manipulated media. Despite the risks, a comprehensive understanding of deepfake detection techniques has not materialized.
Shavez Mushtaq Qureshi, Atif Saeed, Sultan H. Almotiri, Farooq Ahmad, Mohammed A. Al Ghamdi   +4 more
doaj   +2 more sources

Dual-Channel Deepfake Audio Detection: Leveraging Direct and Reverberant Waveforms

IEEE Access
Deepfake content-including audio, video, images, and text-synthesized or modified using artificial intelligence is designed to convincingly mimic real content.
Gunwoo Lee, Jungmin Lee, Minkyo Jung, Joseph Lee, Kihun Hong, Souhwan Jung, Yoseob Han   +6 more
doaj   +1 more source