Results 31 to 40 of about 12,433 (211)

Deepfake Face Generation Techniques Based on Generative Adversarial Networks [PDF]

open access: yesITM Web of Conferences
With the continuous rise of deepfake technology in recent years, deepfake face generation technology has gradually become a popular technology in the field of computer vision.
Pi Yonghe
doaj   +1 more source

Deepfake detection with and without content warnings

open access: yesRoyal Society Open Science, 2023
The rapid advancement of ‘deepfake' video technology—which uses deep learning artificial intelligence algorithms to create fake videos that look real—has given urgency to the question of how policymakers and technology companies should moderate ...
Andrew Lewis   +3 more
doaj   +1 more source

ASVspoof 5: Design, collection and validation of resources for spoofing, deepfake, and adversarial attack detection using crowdsourced speech [PDF]

open access: yesComputer Speech and Language
ASVspoof 5 is the fifth edition in a series of challenges which promote the study of speech spoofing and deepfake attacks as well as the design of detection solutions. We introduce the ASVspoof 5 database which is generated in a crowdsourced fashion from
Xin Wang   +28 more
semanticscholar   +1 more source

DeepFake on Face and Expression Swap: A Review

open access: yesIEEE 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   +5 more
doaj   +1 more source

Deepfakes on Demand: The rise of accessible non-consensual deepfake image generators [PDF]

open access: yesConference on Fairness, Accountability and Transparency
Advances in multimodal machine learning have made text-to-image (T2I) models increasingly accessible and popular. However, T2I models introduce risks such as the generation of non-consensual depictions of identifiable individuals, otherwise known as ...
Will Hawkins   +2 more
semanticscholar   +1 more source

Is Deepfake Diversity Real? Analyzing the Diversity of Deepfake Avatars

open access: yesExpert Systems With Applications
Soon-Gyo Jung   +2 more
exaly   +2 more sources

Diffusion Deepfake

open access: yesCoRR
28 pages including Supplementary ...
Chaitali Bhattacharyya   +4 more
openaire   +2 more sources

Deepfake-Image Anti-Forensics with Adversarial Examples Attacks

open access: yesFuture Internet, 2021
Many deepfake-image forensic detectors have been proposed and improved due to the development of synthetic techniques. However, recent studies show that most of these detectors are not immune to adversarial example attacks.
Li Fan, Wei Li, Xiaohui Cui
doaj   +1 more source

Frequency-Aware Deepfake Detection: Improving Generalizability through Frequency Space Domain Learning

open access: yesAAAI Conference on Artificial Intelligence
This research addresses the challenge of developing a universal deepfake detector that can effectively identify unseen deepfake images despite limited training data.
Chuangchuang Tan   +5 more
semanticscholar   +1 more source

Detection of Frauds in Deep Fake Using Deep Learning

open access: yesEngineering 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   +7 more
doaj   +1 more source

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