Results 21 to 30 of about 1,097 (171)

DeepFake Detection

Proceedings of the 1st Workshop on Security Implications of Deepfakes and Cheapfakes, 2022
AbstractOne particular disconcerting form of disinformation are the impersonating audios/videos backed by advanced AI technologies, in particular, deep neural networks (DNNs). These media forgeries are commonly known as the DeepFakes. The AI-based tools are making it easier and faster than ever to create compelling fakes that are challenging to spot ...
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DEEPFAKE CLI: Accelerated Deepfake Detection Using FPGAs

, 2023
Because of the availability of larger datasets and recent improvements in the generative model, more realistic Deepfake videos are being produced each day. People consume around one billion hours of video on social media platforms every day, and thats why it is very important to stop the spread of fake videos as they can be damaging, dangerous, and ...
Omkar Bhilare, Rahul Singh, Vedant Paranjape, Sravan Chittupalli, Shraddha Suratkar, Faruk Kazi 0001   +5 more
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Understanding the Security of Deepfake Detection

, 2022
Deepfakes pose growing challenges to the trust of information on the Internet. Thus, detecting deepfakes has attracted increasing attentions from both academia and industry. State-of-the-art deepfake detection methods consist of two key components, i.e., face extractor and face classifier, which extract the face region in an image and classify it to be
Xiaoyu Cao, Neil Zhenqiang Gong
openaire   +2 more sources

DeepFake on Face and Expression Swap: A Review

IEEE Access, 2023
Remarkable advances have been made in deep learning, leading to the emergence of highly realistic AI-generated videos known as deepfakes. Deepfakes use generative models to manipulate facial features to create modified identities or expressions with ...
Saima Waseem, Syed Abdul Rahman Syed Abu Bakar, Bilal Ashfaq Ahmed, Zaid Omar, Taiseer Abdalla Elfadil Eisa, Mhassen Elnour Elneel Dalam   +5 more
doaj   +1 more source

FaceSwap based DeepFakes Detection

The International Arab Journal of Information Technology, 2022
The progression of Machine Learning (ML) has introduced new trends in the area of image processing. Moreover, ML presents lightweight applications capable of running with minimum computational resources like Deepfakes, which generates widely manipulated multimedia data.
Marriam Nawaz, Momina Masood, Ali Javed, Tahira Nazir   +3 more
openaire   +1 more source

Detecting Deepfakes with Metric Learning

CoRR, 2020
With the arrival of several face-swapping applications such as FaceApp, SnapChat, MixBooth, FaceBlender and many more, the authenticity of digital media content is hanging on a very loose thread. On social media platforms, videos are widely circulated often at a high compression factor.
Akash Kumar 0004, Arnav Bhavsar
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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

Audio Deepfake Detection: A Survey

CoRR, 2023
Audio deepfake detection is an emerging active topic. A growing number of literatures have aimed to study deepfake detection algorithms and achieved effective performance, the problem of which is far from being solved. Although there are some review literatures, there has been no comprehensive survey that provides researchers with a systematic overview
Jiangyan Yi, Chenglong Wang 0001, Jianhua Tao 0001, Xiaohui Zhang 0006, Chu Yuan Zhang, Yan Zhao   +5 more
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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