Dec 13, 2023 · This study focuses on the deepfake detection of facial images of individual public figures. We propose to condition the proposed detector on the identity of ...
In our approach, the training process involves double neural-network operations where we pass an authentic image through a deepfake simulating network twice.
title={Individualized Deepfake Detection Exploiting Traces Due to Double Neural-Network Operations}, author={Rahman, Mushfiqur and Liu, Runze and Wong, Chau ...
Individualized deepfake detection converts the question "Is this image a deepfake?" to "Is this image a deepfake of that celebrity"? The extra information can ...
Individualized Deepfake Detection Dataset - IEEE DataPort
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Jan 20, 2024 · This dataset contains facial images of 45 specific individuals, divided into train and test sets, including a total of 23k authentic and 22k deepfake images.
DeepFake Detection is the task of detecting fake videos or images that have been generated using deep learning techniques.
Individualized Deepfake Detection Exploiting Traces Due to Double Neural-Network Operations ... This study focuses on the deepfake detection of facial images of ...
In our approach, the training process involves double neural-network operations where we pass an authentic image through a deepfake simulating network twice.
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Nov 20, 2023 · The objective of this paper is to give the reader a better knowledge of (1) how deepfakes are generated and identified, (2) the latest ...
Missing: Individualized | Show results with:Individualized
Most Deepfake detection methods depend on Convolutional Neural Network (CNN)-based models. Spatial and temporal artifacts are exploited to distinguish fake ...
Missing: Individualized Double